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  • 2015-2019  (328)
  • Safari, an O’Reilly Media Company  (328)
  • Därr-Expeditionsservice
  • Edward Elgar Publishing
  • [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc.  (328)
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Language
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Year
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  • 1
    Online Resource
    Online Resource
    What Is Service Design? (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (50 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Companies and their customers today often don’t focus on the same things. While a restaurant may work hard to create an exciting new menu item, diners care more about courtesy. A bank will spend thousands promoting trust while customers struggle to access their website. This report explains how service design can help your organization innovate to deliver great experiences, not just great products, by understanding your customers' needs. Service design experts Adam Lawrence, Marc Stickdorn, Markus Hormeß, and Jakob Schneider explain that service design is a mindset, a process, a toolset, and a cross-disciplinary language. You’ll learn how cross-functional teams can create and orchestrate great customer or employee experiences that satisfy the requirements of the business, the user, and other stakeholders. This report explores how: Service design applies to physical and digital products as well as services Today’s informed customers have created a new challenge for businesses Service design is similar to design thinking and compatible with Agile and Lean Designers can promote low-risk progress through iterative prototyping Lightweight, iterative research can keep teams from solving the wrong problem This approach offers a common language for cross-silo collaboration
    Note: Online resource; Title from title page (viewed August 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492053668/?ar
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 2
    Online Resource
    Online Resource
    Practical Data Science with SAP (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (330 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Learn how to fuse today's data science tools and techniques with your SAP enterprise resource planning (ERP) system. With this practical guide, SAP veterans Greg Foss and Paul Modderman demonstrate how to use several data analysis tools to solve interesting problems with your SAP data. Data engineers and scientists will explore ways to add SAP data to their analysis processes, while SAP business analysts will learn practical methods for answering questions about the business. By focusing on grounded explanations of both SAP processes and data science tools, this book gives data scientists and business analysts powerful methods for discovering deep data truths. You'll explore: Examples of how data analysis can help you solve several SAP challenges Natural language processing for unlocking the secrets in text Data science techniques for data clustering and segmentation Methods for detecting anomalies in your SAP data Data visualization techniques for making your data come to life
    Note: Online resource; Title from title page (viewed September 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492046431/?ar
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 3
    Online Resource
    Online Resource
    Spotlight on Learning from Failure : Assessing Talent Beyond Technical Skills with Tony Tjan (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 57 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: One of the most difficult business challenges has nothing to do with data or technology—it has to do with people. While it’s fairly easy to assess potential hires’ knowledge and skills, it’s much harder to gauge soft traits like attitude. How can you ensure your first impressions are accurate so you can avoid costly hiring mistakes, and correctly identify rising stars and make the most of their talent? Tony Tjan explains how overlooking personality and attitude in favor of technical expertise can cost you. Make sure you’re never in that situation by learning the most important questions to ask during the hiring process to build a stronger, more successful organization. Recorded on March 26, 2019. See the original event page for resources for further learning. Find future live events to attend or watch recordings of other past events . O’Reilly Spotlight explores emerging business and technology topics and ideas through a series of one-hour interactive events. In live conversations, participants share their questions and ideas while hearing the experts’ unique perspectives, insights, fears, and predictions for the future. In every edition of Spotlight on Learning from Failure , you’ll discover the lessons learned from failures both large and small. You’ll discover how successful companies have addressed setbacks, missteps, and challenges and how you can grow from their examples.
    Note: Online resource; Title from title screen (viewed August 27, 2019)
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 4
    Online Resource
    Online Resource
    Programming C# 8.0 (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (801 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local ; Electronic books
    Abstract: C# is undeniably one of the most versatile programming languages available to engineers today. With this comprehensive guide, you’ll learn just how powerful the combination of C# and .NET can be. Author Ian Griffiths guides you through C# 8.0 fundamentals and teaches you techniques for building web and desktop applications. Designed for experienced programmers, this book provides many code examples to help you work with the nuts and bolts of C# code, such as generics, dynamic typing, nullable reference types, and asynchronous programming features. You’ll also get up to speed on ASP.NET, LINQ, and other .NET tools. Discover how C# supports fundamental coding features such as classes, custom types, collections, and error handling Understand the differences between dynamic and static typing in C# Query and process diverse data sources such as in-memory object models, databases, and XML documents with LINQ Use .NET’s multithreading features to exploit your computer’s parallel processing capabilities Learn how the new asynchronous language features can help improve application responsiveness and scalability
    Note: Online resource; Title from title page (viewed December 20, 2019)
    URL: lizenzpflichtig
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    Online Resource
    MPI Ethno. Forsch.
  • 5
    Online Resource
    Online Resource
    Spotlight on Innovation : Predicting the Next Big Breakthrough with Nima Montazeri (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 57 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: With new technologies increasing the pace of innovation every day, companies demand a constant supply of fresh ideas. To be successful, an innovation process must deliver two things: a superior solution and a great market response. Once you have the former, how do you ensure the latter? It all starts by examining the key dimensions of a technology’s evolution and understanding how it’s delighting customers. Learn how to make better decisions about where to focus your innovation efforts and money. You’ll also find out—through two case studies—how backing the right industry innovations can pay off for your organization in a major way. Recorded on April 10, 2019. See the original event page for resources for further learning. Find future live events to attend or watch recordings of other past events . O’Reilly Spotlight explores emerging business and technology topics and ideas through a series of one-hour interactive events. In live conversations, participants share their questions and ideas while hearing the experts’ unique perspectives, insights, fears, and predictions for the future. In every edition of Spotlight on Innovation , you’ll discover what successful companies have in common and how you can follow their lead with small practical steps to transform your organization and prepare for the Next Economy.
    Note: Online resource; Title from title screen (viewed August 29, 2019)
    URL: lizenzpflichtig
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    Online Resource
    MPI Ethno. Forsch.
  • 6
    Online Resource
    Online Resource
    Mastering Spark with R (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (293 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: If you’re like most R users, you have deep knowledge and love for statistics. But as your organization continues to collect huge amounts of data, adding tools such as Apache Spark makes a lot of sense. With this practical book, data scientists and professionals working with large-scale data applications will learn how to use Spark from R to tackle big data and big compute problems. Authors Javier Luraschi, Kevin Kuo, and Edgar Ruiz show you how to use R with Spark to solve different data analysis problems. This book covers relevant data science topics, cluster computing, and issues that should interest even the most advanced users. Analyze, explore, transform, and visualize data in Apache Spark with R Create statistical models to extract information and predict outcomes; automate the process in production-ready workflows Perform analysis and modeling across many machines using distributed computing techniques Use large-scale data from multiple sources and different formats with ease from within Spark Learn about alternative modeling frameworks for graph processing, geospatial analysis, and genomics at scale Dive into advanced topics including custom transformations, real-time data processing, and creating custom Spark extensions
    Note: Online resource; Title from title page (viewed October 11, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492046363/?ar
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 7
    Online Resource
    Online Resource
    Learning Apache OpenWhisk (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (391 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Serverless computing greatly simplifies software development. Your team can focus solely on your application while the cloud provider manages the servers you need. This practical guide shows you step-by-step how to build and deploy complex applications in a flexible multicloud, multilanguage environment using Apache OpenWhisk. You’ll learn how this platform enables you to pursue a vendor-independent approach using preconfigured containers, microservices, and Kubernetes as your cloud operating system. Michele Sciabarrà demonstrates how to build a serverless application using classical design patterns and the programming language or languages that best fit your task. You’ll start by building a simple serverless application hands-on before diving into the more complex aspects of the OpenWhisk platform. Examine how OpenWhisk’s serverless architecture works, including the use of packages, actions, sequences, triggers, rules, and feeds Learn how OpenWhisk compares to existing architectures, such as Java Enterprise Edition Manipulate OpenWhisk features using the command-line interface or a JavaScript API Design applications using common Gang of Four design patterns Use architectural design patterns such as model-view-controller to combine several OpenWhisk actions Learn how to test and debug your code in a serverless environment
    Note: Online resource; Title from title page (viewed July 9, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492046158/?ar
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 8
    Online Resource
    Online Resource
    Practical Time Series Analysis (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (497 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase. Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challengesin time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly. You’ll get the guidance you need to confidently: Find and wrangle time series data Undertake exploratory time series data analysis Store temporal data Simulate time series data Generate and select features for a time series Measure error Forecast and classify time series with machine or deep learning Evaluate accuracy and performance
    Note: Online resource; Title from title page (viewed October 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492041641/?ar
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    Online Resource
    MPI Ethno. Forsch.
  • 9
    Online Resource
    Online Resource
    Load Balancing in Microsoft Azure (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (38 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: With more and more companies moving on-prem applications to the cloud, software and cloud solution architects alike are busy investigating ways to improve load balancing, performance, security, and high availability for workloads. This practical report describes Microsoft Azure’s load balancing options and explains how NGINX can contribute to a comprehensive solution. Cloud solution architect Arlan Nugara takes you through the steps necessary to design a practical solution for your network. Software developers and technical managers will learn how these technologies have a direct impact on application development and architecture. While the examples are specific to Azure, these load balancing concepts and implementations also apply to cloud providers such as AWS, Google Cloud Platform, DigitalOcean, and IBM Cloud. Understand load balancing—what it is and why it’s important Explore load balancing in Azure, including the traffic manager and application gateway Learn how NGINX Plus on Azure lets you create an ideal end-to-end application platform Walk through three load balancing options with Azure and NGINX Plus Explore security choices including NGINX management, NGINX Web Application Firewall, and Azure Firewall integration
    Note: Online resource; Title from title page (viewed July 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492053934/?ar
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 10
    Online Resource
    Online Resource
    Learning CoreDNS (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (203 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Until recently, learning CoreDNS required reading the code or combing through the skimpy documentation on the website. No longer. With this practical book, developers and operators working with Docker or Linux containers will learn how to use this standard DNS server with Kubernetes. John Belamaric, senior staff software engineer at Google, and Cricket Liu, chief DNS architect at Infoblox, show you how to configure CoreDNS using real-world configuration examples to achieve specific purposes. You’ll learn the basics of DNS, including how it functions as a location broker in container environments and how it ties into Kubernetes. Dive into DNS theory: the DNS namespace, domain names, domains, and zones Learn how to configure your CoreDNS server Manage and serve basic and advanced zone data with CoreDNS Configure CoreDNS service discovery with etcd and Kubernetes Learn one of the most common use cases for CoreDNS: the integration with Kubernetes Manipulate queries and responses as they flow through the plug-in chain Monitor and troubleshoot the availability and performance of your DNS service Build custom versions of CoreDNS and write your own plug-ins
    Note: Online resource; Title from title page (viewed September 9, 2019)
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 11
    Online Resource
    Online Resource
    Getting Your Data Ready for AI (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (23 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Despite the enthusiasm for AI, a recent survey reveals that few organizations have adopted this technology in any meaningful way. One reason is the tedious process of accessing, labeling, and transforming data—known as data wrangling—that consumes 80% of a data scientist’s time. There’s a better way to model data. This practical ebook explores a new crop of self-service data preparation tools and services, including IBM Watson Studio, for automating data wrangling. Featuring interviews with data analytics experts, including Alex Castrounis (InnoArchiTech), Jay Limburn (IBM), and Katharine Jarmul ( Data Wrangling with Python ) among others, this ebook examines key barriers to capturing value from AI processes, including problems with data access and preparation. Author Kate Shoup shows data scientists and analysts how Watson Studio and other self-service tools enable domain experts, developers, and business analysts to practice data science. Get an overview of data science and learn how it differs from data analysis Examine a typical AI workflow, including challenges that surface at each step of the data wrangling process Learn solutions to AI workflow challenges, including the use of data catalogs to help you access and prep data Dive into Watson Studio and learn how the platform combines data catalogs with support for data science tools in one environment Evaluate a Watson Studio example and explore real-world use cases
    Note: Online resource; Title from title page (viewed September 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492042419/?ar
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    Online Resource
    MPI Ethno. Forsch.
  • 12
    Online Resource
    Online Resource
    Getting DataOps Right (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (64 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Many large organizations have accumulated dozens of disconnected data sources to serve different lines of business over the years. These applications might be useful to one area of the enterprise, but they’re usually inaccessible to other data consumers in the organization. In this short report, five data industry thought leaders explore DataOps—the automated, process-oriented methodology for making clean, reliable data available to teams throughout your company. Andy Palmer, Michael Stonebraker, Nik Bates-Haus, Liam Cleary, and Mark Marinelli from Tamr use real-world examples to explain how DataOps works. DataOps is as much about changing people’s relationship to data as it is about technology, infrastructure, and process. This report provides an organizational approach to implementing this discipline in your company—including various behavioral, process, and technology changes. Through individual essays, you’ll learn how to: Move toward scalable data unification (Michael Stonebraker) Understand DataOps as a discipline (Nik Bates-Haus) Explore the key principles of a DataOps ecosystem (Andy Palmer) Learn the key components of a DataOps ecosystem (Andy Palmer) Build a DataOps toolkit (Liam Cleary) Build a team and prepare for future trends (Mark Marinelli)
    Note: Online resource; Title from title page (viewed June 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492031765/?ar
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  • 13
    Online Resource
    Online Resource
    Concurrency in C# Cookbook, 2nd Edition (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (251 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local
    Abstract: If you’re one of many developers still uncertain about concurrent and multithreaded development, this practical cookbook will change your mind. With more than 85 code-rich recipes in this updated second edition, author Stephen Cleary demonstrates parallel processing and asynchronous programming techniques using libraries and language features in .NET and C# 8.0. Concurrency is now more common in responsive and scalable application development, but it’s still extremely difficult to code. The detailed solutions in this cookbook show you how modern tools raise the level of abstraction, making concurrency much easier than before. Complete with ready-to-use code and discussions about how and why solutions work, these recipes help you: Get up to speed on concurrency and async and parallel programming Use async and await for asynchronous operations Enhance your code with asynchronous streams Explore parallel programming with .NET’s Task Parallel Library Create dataflow pipelines with .NET’s TPL Dataflow library Understand the capabilities that System.Reactive builds on top of LINQ Utilize threadsafe and immutable collections Learn how to conduct unit testing with concurrent code Make the thread pool work for you Enable clean, cooperative cancellation Examine scenarios for combining concurrent approaches Dive into asynchronous-friendly object-oriented programming Recognize and write adapters for code using older asynchronous styles
    Note: Online resource; Title from title page (viewed August 27, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492054498/?ar
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  • 14
    Online Resource
    Online Resource
    Unblocked (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (274 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Understand the Blockchain Opportunity: No Technical Background Required . Remember thedawn of the internet? The advent of mobile and social media? Yet another digital revolution is nowunderway. Like its predecessors, blockchains are about to transform the way we live, work, and play,while disrupting entrenched industries and shattering conventional business models. Move past the hype and equip yourself to forecast how blockchains will change our world and impactyou and your business. Author Alison McCauley helps non-technical executives to understandhow this technology will trigger change, shift the balance of power, and bring competitiveadvantage to those who know how to leverage them. Unblocked explains: Why ignoring this technology exposes you to competitive disruption What this new technology revolution embraces—no technical background required How to prepare your organization to respond to the coming shift
    Note: Online resource; Title from title page (viewed June 19, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492057963/?ar
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  • 15
    Online Resource
    Online Resource
    TinyML (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (350 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Neural networks are getting smaller. Much smaller. The OK Google team, for example, has run machine learning models that are just 14 kilobytes in size—small enough to work on the digital signal processor in an Android phone. With this practical book, you’ll learn about TensorFlow Lite for Microcontrollers, a miniscule machine learning library that allows you to run machine learning algorithms on tiny hardware. Authors Pete Warden and Daniel Situnayake explain how you can train models that are small enough to fit into any environment, including small embedded devices that can run for a year or more on a single coin cell battery. Ideal for software and hardware developers who want to build embedded devices using machine learning, this guide shows you how to create a TinyML project step-by-step. No machine learning or microcontroller experience is necessary. Learn practical machine learning applications on embedded devices, including simple uses such as speech recognition and gesture detection Train models such as speech, accelerometer, and image recognition, you can deploy on Arduino and other embedded platforms Understand how to work with Arduino and ultralow-power microcontrollers Use techniques for optimizing latency, energy usage, and model and binary size
    Note: Online resource; Title from title page (viewed December 25, 2019)
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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  • 16
    Online Resource
    Online Resource
    The Experience-Centric Organization (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (266 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Is your organization prepared for the next paradigm of customer experience, or will you be left behind? This practical book will make you a winner in a market driven by experience, enabling you to develop desirable offerings and standout service to attract loyal customers. Author Simon Clatworthy shows you how to transform your organization into one that aligns your customers’ experiential journey with platforms, organizational structures, and strategic alliances. Rather than treat customer experience as an add-on to product and service design, you’ll discover how experience-centricity can drive the whole organization. Learn the five steps necessary to transform into an experience-centric organization Explore the underlying structure needed to design and deliver memorable experiences Understand how customers and clients experience products and services Develop experiential DNA as an extension of your brand DNA Be proactive by translating cultural trends into experiences
    Note: Online resource; Title from title page (viewed July 15, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492045762/?ar
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  • 17
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    Online Resource
    Spotlight on Innovation : Succeeding with Machine Learning with Alex Jaimes (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 58 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Machine learning (ML) is absolutely critical to driving your business success—and more opportunities to integrate it in innovative ways are emerging every day. However, implementation isn’t always as easy as it seems. To effectively execute ML and make it work for your organization, you must solve for this new interdependency between data, metrics, and testing. In this Spotlight on Innovation , learn about machine learning opportunities and challenges—and why process improvements can be even more beneficial than algorithmic ones. Recorded on February 13, 2019. See the original event page for resources for further learning. Find future live events to attend or watch recordings of other past events . O’Reilly Spotlight explores emerging business and technology topics and ideas through a series of one-hour interactive events. In live conversations, participants share their questions and ideas while hearing the experts’ unique perspectives, insights, fears, and predictions for the future. In every edition of Spotlight on Innovation , you’ll discover what successful companies have in common and how you can follow their lead with small practical steps to transform your organization and prepare for the Next Economy.
    Note: Online resource; Title from title screen (viewed July 30, 2019)
    URL: lizenzpflichtig
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    MPI Ethno. Forsch.
  • 18
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    Online Resource
    Spotlight on Innovation : The Future Beyond Digital—Entering a New Era of Exploration and Collaboration with Greg Satell (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 56 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Innovation isn’t just about solving existing problems faster and more efficiently; it’s about discovering and solving new ones. To remain competitive, today’s business leaders need to embrace not only new technologies but an entirely new mindset when it comes to innovation. Recorded on November 28, 2018. See the original event page for resources for further learning. Find future live events to attend or watch recordings of other past events . O’Reilly Spotlight explores emerging business and technology topics and ideas through a series of one-hour interactive events. In live conversations, participants share their questions and ideas while hearing the experts’ unique perspectives, insights, fears, and predictions for the future. In every edition of Spotlight on Innovation , you’ll discover what successful companies have in common and how you can follow their lead with small practical steps to transform your organization and prepare for the Next Economy.
    Note: Online resource; Title from title screen (viewed August 1, 2019)
    URL: lizenzpflichtig
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  • 19
    Online Resource
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    Spotlight on Data : Data Storytelling with Mico Yuk (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 56 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: The power of storytelling has long been used in Hollywood to engage viewers and generate billions of dollars in sales. However, data storytelling, while highly trendy, is frequently misused and often limited to pretty charts. In this Spotlight on Data , learn how to use the power of storytelling with your data to skyrocket user engagement. Get your users to take action by implementing a few proven techniques. Recorded on July 15, 2019. See the original event page for resources for further learning. Find future live events to attend or watch recordings of other past events . O’Reilly Spotlight explores emerging business and technology topics and ideas through a series of one-hour interactive events. In live conversations, participants share their questions and ideas while hearing the experts’ unique perspectives, insights, fears, and predictions for the future. In every edition of Spotlight on Data , you’ll learn about, discuss, and debate the tools, techniques, questions, and quandaries in the world of data. You’ll discover how successful companies leverage data effectively and how you can follow their lead to transform your organization and prepare for the Next Economy.
    Note: Online resource; Title from title screen (viewed July 30, 2019)
    URL: lizenzpflichtig
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  • 20
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    Spotlight on Data : Caching Big Data for Machine Learning at Uber with Zhenxiao Luo (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 1 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: From determining the most convenient rider pickup points to predicting the fastest routes, Uber uses data-driven machine learning to create seamless trip experiences. Within engineering, big data and machine learning inform decision-making processes across the board. As Uber expands to new markets, the ability to accurately and quickly use data to make predictions becomes even more important. In this case study, Uber’s Zhenxiao Luo details the company's machine learning architecture and talk about how Uber uses big data to power machine learning jobs. Recorded on June 17, 2019. See the original event page for resources for further learning. Find future live events to attend or watch recordings of other past events . O’Reilly Spotlight explores emerging business and technology topics and ideas through a series of one-hour interactive events. In live conversations, participants share their questions and ideas while hearing the experts’ unique perspectives, insights, fears, and predictions for the future. In every edition of Spotlight on Data , you’ll learn about, discuss, and debate the tools, techniques, questions, and quandaries in the world of data. You’ll discover how successful companies leverage data effectively and how you can follow their lead to transform your organization and prepare for the Next Economy.
    Note: Online resource; Title from title screen (viewed October 4, 2019)
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    Random search and reproducibility for neural architecture search (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 41 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Neural architecture search (NAS) is a promising research direction that has the potential to replace expert-designed networks with learned, task-specific architectures. Ameet Talwalkar (Carnegie Mellon University Determined AI) shares work that aims to help ground the empirical results in this field and proposes new NAS baselines that build off the following observations: NAS is a specialized hyperparameter optimization problem, and random search is a competitive baseline for hyperparameter optimization. Leveraging these observations, Ameet evaluates both random search with early-stopping and a novel random search with a weight-sharing algorithm on two standard NAS benchmarks: PTB and CIFAR-10. Results show that random search with early-stopping is a competitive NAS baseline that performs at least as well as ENAS, a leading NAS method, on both benchmarks. Additionally, random search with weight-sharing outperforms random search with early-stopping, achieving a state-of-the-art NAS result on PTB and a highly competitive result on CIFAR-10. Ameet concludes by exploring existing reproducibility issues for published NAS results, noting the lack of source material needed to exactly reproduce these results, and discussing the robustness of published results given the various sources of variability in NAS experimental setups. All information (code, random seeds, documentation) needed to exactly reproduce our results will be shared, along with random search with weight-sharing results for each benchmark on two independent experimental runs. This session was recorded at the 2019 O'Reilly Artificial Intelligence Conference in New York.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    Programming iOS 13 (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1000 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: If you’re grounded in the basics of Swift, Xcode, and the Cocoa framework, this book provides a structured explanation of all essential real-world iOS app components. Through deep exploration and copious code examples, you’ll learn how to create views, manipulate view controllers, and add features from iOS frameworks. Create, arrange, draw, layer, and animate views that respond to touch Use view controllers to manage multiple screens of interface Master interface classes for scroll views, table views, text, popovers, split views, web views, and controls Dive into frameworks for sound, video, maps, and sensors Access user libraries: music, photos, contacts, and calendar Explore additional topics, including files, networking, and threads
    Note: Online resource; Title from title page (viewed December 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492074601/?ar
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    Product Design vs. Design Thinking (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Product design tends to jump between business thinking and creative thinking, but design thinking blends them together. This infographic describes the skillset and processes behind product design and design thinking.
    Note: Online resource; Title from title page (viewed July 15, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492031888/?ar
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    Product Management (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: How does a product manager successfully connect and align their team? By leveraging the CORE skills of product management: communication, organization, research, and execution. This infographic describes the core skills needed for a product manager to succeed at your organization.
    Note: Online resource; Title from title page (viewed May 19, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492036159/?ar
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    Practical Deep Learning for Cloud, Mobile, and Edge (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (618 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach. Relying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use. Train, tune, and deploy computer vision models with Keras, TensorFlow, Core ML, and TensorFlow Lite Develop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google Coral Explore fun projects, from Silicon Valley’s Not Hotdog app to 40+ industry case studies Simulate an autonomous car in a video game environment and build a miniature version with reinforcement learning Use transfer learning to train models in minutes Discover 50+ practical tips for maximizing model accuracy and speed, debugging, and scaling to millions of users
    Note: Online resource; Title from title page (viewed October 17, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492034858/?ar
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    O'Reilly Velocity Conference 2019 - Berlin, Germany (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 2 hr., 58 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: We’ll make the Keynotes available here as soon as possible after they happen. Video of the sessions and tutorials will be available a few weeks after the end of the conference. O'Reilly Velocity Conferences are devoted to providing its international audience of SREs, app developers, DevOps practitioners, systems architects, CTOs, and CIOs with the most on-point training and information possible on how to build and maintain large-scale cloud native systems. Velocity Berlin 2019 stayed true to this formula. It gathered some of the world's top cloud practitioners to share their expertise and insights on key concepts like Kubernetes, site reliability engineering, observability, and performance. Stay ahead of your competition, get this video compilation, and enjoy a front-row seat to all of the best that Velocity Berlin 2019 had to offer. Highlights include: Unrestricted access to hours of the best presentations from Velocity Berlin 2019—this video compilation includes keynote sessions, deep-dive tutorials, and technical sessions. Kubernetes sessions, including Jonathan Johnson's (Dijure LLC) intro to Kubernetes tutorial; Jose Nino’s (Lyft) look at deploying hybrid topologies with Kubernetes and Envoy; and Bastian Hofmann’s (SysEleven) talk on using Kubernetes to deploy an application across multiple clusters in different regions. Monitoring, Observability, and Performance sessions, such as Liz Fong-Jones (Honeycomb) on how microservice-based systems do distributed tracing using OpenTelemetry; Lorenzo Fontana (Sysdig) on eBPF-powered distributed Kubernetes performance analysis; and Nathanael Jean-Francois (NS1) on using BGP edge optimizations to measure internet performance and make routing decisions. Overcoming Obstacles/Lessons in Resilience sessions, including Alois Reitbauer’s (Dynatrace Software) cautions on how to ensure that delivery pipeline automation code won’t devolve into legacy code and Josh Michielsen’s (Condé Nast International) insider’s take on the lessons learned from operating a Kubernetes driven global cloud native platform. Building Secure Systems sessions like Jennifer Davis’ (Microsoft) survey of the cloud security tools and practices everyone should. Building Resilient Systems sessions, such as Jenn Strater’s (Gradle) guide to using data to better debug build errors, speed up individual runs, and make a happy release process, or Heidi Waterhouse’s (LaunchDarkly) reveal of the often overlooked factors that dramatically affect...
    Note: Online resource; Title from title screen (viewed November 6, 2019)
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    O'Reilly Software Architecture Conference 2019 - San Jose, California (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 63 hr., 23 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: The O'Reilly Software Architecture Conference San Jose 2019 (SACON) gathered the world's leading software architects and engineers to give presentations on software architecture's most useful technologies, trends, and techniques. This video compilation gives you complete access to the best of SACON's keynotes, tutorials, and technical sessions. It contains hours of material to review and study at your own pace. Whether you are optimizing legacy systems or migrating to cloud native architecture, this compilation from SACON San Jose 2019 offers you the insights and training you need to get to the next level. Highlights include: Contains hours of video recordings from the best of SACON San Jose 2019's keynotes, tutorials, and technical sessions. 3.5 hour tutorials like Christian Hernandez's (Red Hat) hands-on introduction to Kubernetes and OpenShift; Nathaniel Schutta's (Pivotal) deep dive into trade-off analysis and how to use it to strategically choose the correct technology for your projects; and Valentina Rodriguez's (Independent) reveal of the twelve essential principles of architecture design in Agile environments. Keynotes from Rebecca Wirfs-Brock (Wirfs-Brock Associates), Michael Feathers (R7K Research and Conveyance), Adam Tornhill (Empear), Rebecca Parsons (ThoughtWorks), and Neal Ford (ThoughtWorks). Application Architecture sessions, such as Stefania Stefansdottir's (ThoughtWorks) walk through of the practices all new architects and tech leads should keep in mind when starting a new project; Ian Varley (Salesforce) on spotting and correcting the cognitive biases that undermine your software architecture; and Andrew Bonham and Thiagarajan Subramanian's (Capital One) review of how to use reactive architecture and microservices, machine learning, H20, Akka, and Kafka. Microservices sessions, including Kasun Indrasiri's (WSO2) in-depth overview of common microservice resiliency patterns such as timeout, retry, circuit breaker, fail-fast, bulkhead, transactions, and more; Nathaniel Schutta (Pivotal) on the factors used to decide if something deserves to be a microservice or not; and Samir Behara (EBSCO) on building scalable microservice architectures with Envoy, Kubernetes, and Isti. Enterprise Architecture sessions, including Heidi Waterhouse (Launch Darkly) on the smartest ways to achieve build-versus-buy decisions; Cat Swetel (Ticketmaster) on using value network mapping and real options theory to evolve monolithic software; and Paula ...
    Note: Online resource; Title from title screen (viewed June 13, 2019)
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    O'Reilly Artificial Intelligence Conference 2019 - London, United Kingdom (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 2 hr., 37 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: We’ll make the Keynotes available here as soon as possible after they happen. Video of the sessions and tutorials will be available a few weeks after the end of the conference. The Artificial Intelligence Conference London 2019 gathered some of the globe's top AI practitioners to speak about AI's most promising developments, emerging technologies, and profitable use cases. This video compilation provides you with the best that AI London 2019 had to offer. It includes thought provoking presentations from such AI luminaries as Ariadna Font Llitjós, the director of engineering at Twitter’s Cortex Machine Learning Platform; Martin Goodson, the chief scientist at Evolution AI; Jeff Jonas, the founder and CEO of Senzing; Kim Hazelwood, the senior engineering manager who leads AI infrastructure research efforts at Facebook, and many more of AI’s top data scientists, software engineers, and business strategists. AI is changing fast and it’s transforming business even faster. To see where AI is going (and the entirely new business models and procedures it enables), get this compilation and you’ll be ahead of the curve. Highlights include: Complete video recordings of AI London 2019’s best keynotes, tutorials, and technical sessions—this compilation contains hours of material to study, review, and absorb at your own pace. Keynote presentations from AI’s most notable thinkers, including Intels’ Alexis Crowell Helzer, IBM’s Ritika Gunnar, Dell Technologies’ Arash Ghazanfari, and more. Hours of fact-packed AI, ML, and DL tutorials from top AI practitioners like Robert Crowe (Google) on ML pipelines, TensorFlow Extended pipelines, and ML production deployment issues; Danielle Dean (iRobot) on training and deploying Python models in Azure; and Sergey Ermolin (AWS) on how to use reinforcement learning to build recommendation systems with AWS SageMaker RL. Members-only access to every AI Business Summit Executive Briefing/Best Practices session: Twenty hard-nosed presentations that provide an insider’s look at the AI implementations that will impact your business the most. Implementing AI sessions, including Carlos Rodrigues's (Siemens) look at how Siemens fights cybercrime with AI; Alex Ingerman's (Google) introduction to Federated ML, a new decentralized form of ML; Siddha Ganju's (NVIDIA) discussion of how to set-up deep learning on mobile devices; and Thomas Phelan (HPE BlueData) on how to spin up GPU-enabled AI, ML, and DL clusters in Docker containers...
    Note: Online resource; Title from title screen (viewed October 16, 2019)
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    O'Reilly Strata Data Conference 2019 - New York, New York (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 149 hr., 54 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: The 2019 Strata Data Conference NYC, the biggest Big Data conference in the world, was a massive success. Packed with thousands of attendees, Strata gathered the world's top data practitioners to provide expert guidance on the tools and technologies you need to make your data strategies and projects work today. This video compilation holds the best of Strata NYC 2019's keynotes, tutorials, and technical sessions. Looking for a head start on the data techniques and technologies you need to succeed? This compilation points the way forward by offering you hours of material to study and absorb at your own rate. The compilation includes such gems as Data Engineering and Architecture sessions, where you'll learn how to select the right type of data infrastructure and architecture to streamline your workflows, reduce costs, and scale your data analysis; Data Science, Machine Learning (ML) and AI sessions, where you'll learn how to use text mining, real-time analytics, large-scale anomaly detection and other techniques to discover the hidden insights in your data; and all of the best talks from the Strata Business Summit, where you'll receive an insiders-only look at the processes and technologies some of the world's most successful companies used to develop their own data strategies. Highlights include: A front row seat at 2019's Strata Data Conference NYC best keynotes, tutorials, and technical sessions—contains hundreds of hours of material to study and absorb at your own pace. Keynote speeches from Big Data's most inspiring business visionaries, such as Sara Menker (CEO, Gro Intelligence), Cassie Kozyrkov (Chief Decision Scientist, Google Cloud), Swatee Singh (VP Big Data/ML, American Express), and Robert D. Thomas (GM, IBM Data and AI). Deep dive tutorials including Jules Damji's (Databricks) sold out session on managing the complete ML lifecycle with MLflow; Karthik Ramasamy's (Streamlio) review of serverless streaming architectures and algorithms for the enterprise; and Mark Donsky (Okera) on how to secure your data lakes to meet the rigors of CCPA privacy regulations. Data Engineering and Architecture sessions, including Navinder Pal Singh Brar (Walmart Labs) on building multitenant data processing and model inferencing platforms with Kafka Streams; Paige Roberts (Vertica) on the whys and hows of putting large stateful applications into containers and Kubernetes; Tomer Levi (Fundbox) on using AWS Step Functions, Docker containers, and ECS Farg...
    Note: Online resource; Title from title screen (viewed September 25, 2019)
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    Navigating the Continuous Delivery Pipeline (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Continuous delivery (CD) is a key component of the DevOps workflow that enables you to make code changes and release new features quickly, effectively, and reliably. The CD pipeline includes six high-level stages, each with corresponding tools and processes that leverage automation to ensure fast feedback. Manual or automated handoffs trigger a new stage or process, and DevOps engineers work collaboratively through the cycle. This infographic describes the DevOps cycle and how your organization can navigate that effectively.
    Note: Online resource; Title from title page (viewed July 15, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492031949/?ar
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    Multicloud Architecture Migration and Security (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (56 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: If you’re considering a multicloud approach to host applications, you’re in good company. According to a recent survey, 42% of the world’s organizations have adopted this strategy. But there are significant challenges and complexities to overcome. This practical report walks you through the pros and cons of migrating to these environments, particularly for securing your applications. Cybersecurity experts Laurent Gil and Allan Liska show you how to orchestrate and manage multicloud environments, including edge technologies designed to secure and protect your environment. Managers and leaders will learn methods for distributing workloads across cloud providers as well as ways to avoid potential pitfalls when pursuing this strategy. Understand the benefits of adopting a multicloud architecture—along with the trade-offs and short-term costs Learn how orchestration lets you manage dozens of applications across thousands of containers in a multicloud environment Explore ways to apply a consistent security policy across all cloud platforms Implement layered security that includes vulnerability scanning, API gateway deployment, and web application firewalls Delve into specific use cases for delivering web application security across all cloud providers
    Note: Online resource; Title from title page (viewed November 5, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492050407/?ar
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    Interpretable and resilient AI for financial services (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 48 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Financial services are increasingly deploying AI models and services for a wide range of applications in the credit lifecycle, such as credit onboarding and identifying transaction fraud and identity fraud. These models must be interpretable, explainable, and resilient to adversarial attacks. In some situations, regulatory requirements apply that prohibit black-box machine learning models. Jari Koister (FICO) shares forward-looking tools and infrastructure has developed to support these needs. Topics include: Examples of financial services applications of AI and ML Specific needs for explainability and resiliency Approaches for solving explainability and resiliency Regulatory requirements and how to meet them A platform that provide support for xAI and mission-critical AI Further research and product development directions This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 2nd Edition (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (848 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local
    Abstract: Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use Scikit-Learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets
    Note: Online resource; Title from title page (viewed September 30, 2019)
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    Getting Started with Machine Learning in the Cloud (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (36 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Your company creates terabytes and even petabytes of data, but are you actually putting it to work? The majority of enterprises stumble on their way to becoming data driven. Machine learning promises to reverse that trend, and early adopters are already seeing the benefits with increased ROI. In this report, author Alice LaPlante details successful real-world applications for machine learning and shows you how to implement your own machine learning initiative step-by-step. Discover how machine learning can benefit your business and see how companies such as CaixaBank and DX Marketing use machine learning to their advantage. Don’t fall behind while early adopters reap all the gains. Get started with machine learning and tame your data. You’ll learn: Machine learning use cases, including recommendation engines, fraud detection, predictive maintenance, and more The benefits of machine learning Why companies are increasingly moving machine learning implementations to the cloud The six phases of the machine learning lifecycle A five-step process to getting started with machine learning The challenges you may encounter along the way Best practices and advice from early adopters
    Note: Online resource; Title from title page (viewed November 25, 2019)
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    Game engines and machine learning (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 42 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Games are wonderful contained problem spaces, making them great places to explore AI—even if you’re not a game developer. Paris Buttfield-Addison (Secret Lab Pty. Ltd.), Mars Geldard (University of Tasmania), and Tim Nugent (lonely.coffee) teach you how to use Unity to train, explore, and manipulate intelligent agents that learn. You’ll train a quadruped to walk, then train it to explore, fetch, and manipulate the world. It’s a little bit technical, a little bit creative. Join Paris, Mars, and Tim to learn how to use game technologies such as Unity to further your understanding of machine learning fundamentals and solve problems. Topics include: How video game engines are a perfect environment to constrain a problem and train an agent How easy it is to get started, using Unity How to build up a model and use it in the engine to explore a particular idea or problem This session was recorded at the 2019 O'Reilly Artificial Intelligence Conference in New York.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    Getting Started with Ghidra (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (39 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: There’s a powerful new tool in the fight against malware. The US National Security Agency (NSA) recently released its reverse engineering framework, Ghidra, as free and open source software. This practical report explains how engineers can use Ghidra to analyze malware and determine its impact on vulnerable systems. Developers can also use this tool to get a detailed look at compiled programs. Information security experts Ric Messier and Matthew Berninger show you how Ghidra helps you to analyze compiled code on Linux, Windows, and macOS. You’ll be able to visually inspect a program, follow the path of execution, and analyze the code from function call to function call. The more you work with Ghidra, the more you’ll understand how effective this platform is. Get a feature overview of Ghidra, including a quick look into its origins Explore program use cases, including malware analysis, compiler comparison, and efficiency improvements Learn the advantages of running this Java-based framework in a container Perform code analysis by disassembling and graphing a program using Ghidra’s CodeBrowser tool Run Ghirdra on innocuous programs before analyzing code that may be infected
    Note: Online resource; Title from title page (viewed October 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781098115265/?ar
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    Fraud detection without feature engineering (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 40 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: In many industrial ML applications, feature engineering consumes the lion’s share of time, energy, and resources. Deep learning promises to replace feature engineering with models that learn end to end from “close-to-reality” data and has convincingly realized this promise for computer vision and natural language processing. But does this promise apply outside of these domains? Pamela Vagata (Stripe) explains how Stripe has applied deep learning techniques to predict fraud from raw behavioral data. Since fraud detection is a critical business problem for Stripe, the company already had a well-tuned feature-engineered model for comparison. Stripe found that the deep learning model outperforms the feature-engineered model both on predictive performance and in the effort spent on data engineering, model construction, tuning, and maintenance. Join in to discover how common industry practice could shift toward deeper models trained end to end and away from labor-intensive feature engineering. This session was recorded at the 2019 O'Reilly Artificial Intelligence Conference in New York.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    Executive Briefing : Why machine-learned models crash and burn in production and what to do about it (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 37 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Much progress has been made over the past decade on process and tooling for managing large-scale, multitier cloud apps and APIs, but there is far less common knowledge on best practices for managing machine-learned models (classifiers, forecasters, etc.), especially beyond the modeling, optimization, and deployment process once these models are in production. A key mindset shift required to address these issues is understanding that model development is different than software development in fundamental ways. David Talby (Pacific AI) shares real-world case studies showing why this is true and explains what you can do about it, covering key best practices that executives, solution architects, and delivery teams must take into account when committing to successfully deliver and operate data science-intensive systems in the real world. Topics include: Concept drift (Machine-learned models begin degrading as soon as they’re deployed and must adapt to a changing environment.) Locality and limited reuse and generalization of models A/B testing challenges, which make it very hard in practice to know which model will perform better in production Semisupervised and adversarial learning scenarios, which require modeling and optimizing models only once they’re in production The impact of all of the above on product planning, staffing, and client expectation management This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    Engineering Reliable Mobile Applications (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (35 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Imagine a situation where your service reports as healthy and serving but you receive multiple user reports of poor availability. How are these users accessing your service? Most likely, they’re using a client application, such as a mobile phone. Traditionally, SRE has only supported systems and services running in data centers rather than code running on the client, which has impeded issue detection. This report examines the challenges of client-side reliability and provides a useful set of SRE concepts and tools you can apply to your own apps. Four site reliability engineers from Google share their experiences developing and supporting first-party native mobile applications. You’ll learn core concepts critical to engineering reliable client apps as well as phenomena unique to mobile applications and key takeaways from issues caused by or related to them, including: Designing mobile apps that are resilient to unexpected inputs Rolling out changes in a controlled, metric-driven way Monitoring apps in production by measuring critical user interactions Releasing changes using feature flags so they can be evaluated and rolled back independently Understanding and preparing for your app’s impact on servers Using practices that avoid feedback patterns between your apps and services
    Note: Online resource; Title from title page (viewed July 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492057444/?ar
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    Disrupting data discovery (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 42 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Before any analysis can begin, a data scientist needs to discover the right data sources to analyze, understand them, and determine whether they can trust them. Unfortunately, data discovery is very inefficient today. Countless hours are lost trying to find the right data to use. (The most common way still remains to ask a coworker.) Gaining trust in data requires running a bunch of queries (max timestamp, counts per day, count distincts, etc.) that waste time and add unnecessary load on the databases. There’s no clear way to know how to find folks to answer questions about the table. And worst of all, many times analysis is redone and models are rebuilt because previous work isn’t discoverable. Lyft has reduced the time it takes to discover data by 10x by building its own data portal, Amundsen. Amundsen is built on three key pillars: an augmented data graph, an intuitive user experience, and centralized metadata. Amundsen uses a graph database under the hood to store relationships between various data assets (tables, dashboards, protobuf events, etc.). What’s unique to Amundsen is that it treats people as a first-class data asset; in other words, there’s a graph node for each person in the organization that connects to other nodes (like tables, and dashboards). In addition, Amundsen runs PageRank using data from access logs to power search ranking, similar to how Google ranks web pages on the internet. Finally, Amundsen gathers metadata from various different sources (Hive, Presto, Airflow, etc.) and exposes it in one central place. The right place to store all this metadata is a work in progress. Mark Grover and Tao Feng (Lyft) offer a demo of Amundsen and lead a deep dive into its architecture, covering how it leverages centralized metadata, page rank, and a comprehensive data graph to achieve its goal. They also explore the future roadmap, unsolved problems, and its collaboration model. This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    Building Your Cloud Strategy (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (2 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Cloud computing is the practice of storing data, software, and services online so you can access and consume them remotely over the internet. This infographic describes the options and benefits of cloud computing as well as the common deployment models.
    Note: Online resource; Title from title page (viewed July 15, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492040064/?ar
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    Building enterprise data products (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 44 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Much of the hardest work of creating effective data products in the enterprise is not in the complexity of the algorithms applied but in effective design and integration into downstream systems. Hilary Mason (Cloudera) shares a process for repeatedly creating effective AI products, from idea through process to specific design considerations, and explains how architecture and algorithmic choices can support or hinder this process. This session was recorded at the 2019 O'Reilly Artificial Intelligence Conference in New York.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    Bringing data to life : Combining machine learning and art to tell a data story (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 24 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Analytics and AI are powerful methods for extracting insights hidden in data. However, these methods by themselves cannot convey insights. Visualization is a key requirement for explaining analytical findings, but visualizations such as graphs and charts are not always enough to explain data, especially to a nontechnical audience. This audience may need a different approach to connect with the data. Nancy Rausch (SAS Institute) shares a case study for a project that combined machine learning and art to tell a big data story. She explains how she and her team collected and prepared IoT streaming data from a solar array farm, applied an analytical model to forecast future output, and then visualized the results for general audiences using interactive art. They also used artificial intelligence and natural language processing to allow visitors to interact with the art installation. The project brought solar array technology to life in a way that was able to engage and delight visitors of all ages and backgrounds. This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    Applied machine learning in finance - 2019 O'Reilly Strata Data Conference, San Francisco (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 34 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Quantitative finance is a rich field in finance where advanced mathematical and statistical techniques are employed by both sell-side and buy-side institutions. Techniques like time series analysis, stochastic calculus, multivariate statistics, and numerical optimization are often used by “quants” for modeling asset prices, portfolio construction and optimization, and building automated trading strategies. Chakri Cherukuri (Bloomberg LP) explains how machine learning and deep learning techniques are being used in quantitative finance. Chakri outlines use cases for machine learning in finance and dives into a few examples, involving both structured and unstructured datasets, to examine in detail how machine learning models can be used for predictive analytics. Chakri details how these models work under the hood and explores the interpretability of these models. Along the way, you’ll look at novel interactive visualizations and diagnostic plots that will help you better understand these models.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    An architect's guiding principles for leadership (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 44 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Architects are leaders. We need to understand our business, our users, and our ecosystem. We need to effectively interact with our stakeholders, productively collaborate with design and product teams, and give direction and motivate our development teams. Achieving these goals requires much more than technical excellence. Seth Dobbs (Bounteous) shares a primer on leadership for architects, focusing on guiding principles that are easy to learn and put into practice. Principles cover both inward focus (personal mastery) and external focus (effective interactions) and include topics such as vision, problem solving, ownership, and conflict. Seth explores material he’s used to train team members ranging from developers and designers up into the executive level but focuses on core guiding principles specific to helping architects be more effective in their roles. Each principle will be presented first with a problem or anti-pattern, then the principle, and then examples of the principle in practice. This approach should be valuable whether you are new in a leadership role and looking to understand the “soft” skills required or have been leading for a while and want to formalize your thinking on leadership. This session was recorded at the 2019 O'Reilly Software Architecture Conference in San Jose.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    What Is Blockchain? (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (46 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Everyone’s talking about blockchain. This exciting technology has the potential to impact our lives in much the same way as the internet did, but few understand how it actually works. Written for business technology leaders, this report breaks down the complexity of blockchain into plain language and simple illustrations so you can easily explain it to your colleagues. Sir John Hargrave and Evan Karnoupakis go beyond the hype to help you discover valuable opportunities for using blockchain in your business. The practical examples in this report will inspire you to get started on your own project; the real-world lessons will ensure you get it right. Understand the building blocks of blockchain, including the decentralized ledger, nodes, consensus protocols, and smart contracts Get up to speed on basic blockchain concepts, such as mining, forking, governance, and regulation Learn the power of the Blockchain Network Effect, the mystery of the Consensus Paradox, and other key blockchain principles Discover the challenges to setting up a blockchain project, plus four simple best practices to succeed
    Note: Online resource; Title from title page (viewed October 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781098114749/?ar
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    Programming PyTorch for Deep Learning (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (217 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Deep learning is changing everything. This machine learning method has already surpassed traditional computer vision techniques, and the same is happening with NLP. If you're looking to bring deep learning into your domain, this practical book will bring you up to speed on key concepts using Facebook's PyTorch framework. Once author Ian Pointer helps you set up PyTorch on a cloud-based environment, you'll learn how use the framework to create neural architectures for performing operations on images, sound, text, and other types of data. By the end of the book, you'll be able to create neural networks and train them on multiple types of data. Learn how to deploy deep learning models to production Explore PyTorch use cases in companies other than Facebook Learn how to apply transfer learning to images Apply cutting-edge NLP techniques using a model trained on Wikipedia
    Note: Online resource; Title from title page (viewed September 27, 2019)
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    MongoDB : The Definitive Guide, 3rd Edition (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (425 pages)
    Edition: 3rd edition
    Keywords: Electronic books ; local ; MongoDB ; NoSQL-Datenbanksystem
    Abstract: With Early Release ebooks, you get books in their earliest form—the author's raw and unedited content as he or she writes—so you can take advantage of these technologies long before the official release of these titles. Manage your data in a database system designed to support modern application development. The updated edition of this authoritative and accessible guide shows you the many advantages of using document-oriented databases, including how this secure, high-performance system enables flexible data models, high availability, and horizontal scalability. Written by current and former members of the MongoDB team, the third edition is updated for MongoDB 4.0. You’ll find substantial updates on querying, indexing, aggregation, replica sets, ops manager, sharding administration, data administration, durability, monitoring, and security. Authors Shannon Bradshaw (MongoDB) and Kristina Chodorow (Google) provide guidance for database developers, advanced configuration for system administrators, and use cases for a variety of projects. Ideal for NoSQL newcomers and experienced MongoDB users alike, this book also includes many real-world schema design examples.
    Note: Online resource; Title from title page (viewed June 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781491954454/?ar
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    Product Roadmaps Relaunched (Audio Book) (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (21944 pages)
    Edition: 1st edition
    Keywords: Audiobooks ; local
    Abstract: A good product roadmap is one of the most important and influential documents an organization can develop, publish, and continuously update. In fact, this one document can steer an entire organization when it comes to delivering on company strategy. This practical guide teaches you how to create an effective product roadmap, and demonstrates how to use the roadmap to align stakeholders and prioritize ideas and requests. With it, you’ll learn to communicate how your products will make your customers and organization successful. Whether you're a product manager, product owner, business analyst, program manager, project manager, scrum master, lead developer, designer, development manager, entrepreneur, or business owner, this audio book will show you how to: Articulate an inspiring vision and goals for your product Prioritize ruthlessly and scientifically Protect against pursuing seemingly good ideas without evaluation and prioritization Ensure alignment with stakeholders Inspire loyalty and over­-delivery from your team Get your sales team working with you instead of against you Bring a user­ and buyer-­centric approach to planning and decision-making Anticipate opportunities and stay ahead of the game Publish a comprehensive roadmap without over­committing
    Note: Online resource; Title from title page (viewed March 28, 2019)
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    Introducing Istio Service Mesh for Microservices, 2nd Edition (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (83 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local
    Abstract: Microservices fundamentally change the way you design enterprise software. By adding network dependencies to your application logic, you invite in a host of potential hazards that grow proportionally with the number of connections you make. With the updated edition of this practical ebook, application architects and development team leads will learn how to use the Istio service mesh to connect, manage, and secure microservices in order to create powerful cloud-native applications. Burr Sutter and his team at Red Hat introduce you to several key microservices capabilities that Istio provides on top of Kubernetes and OpenShift. You’ll learn how your application can offload service discovery, load balancing, resilience, observability, and security to Istio so you can focus on differentiating business logic. Dive into Istio with detailed examples of: Traffic control: Examine Istio patterns including smarter canaries and dark launches Service resiliency: Discover how Istio provides load balancing, circuit breaking, and pool ejection Chaos testing: Test your system’s ability to withstand turbulent conditions through fault injection Observability: Use tracing and metrics to learn the relationships between individual system components Security: Explore Istio’s security capabilities, such as mTLS, RBAC, and policy enforcement
    Note: Online resource; Title from title page (viewed July 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492052630/?ar
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    Building Intelligent Cloud Applications (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (154 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Serverless computing is radically changing the way we build and deploy applications. With cloud providers running servers and managing machine resources, companies now can focus solely on the application’s business logic and functionality. This hands-on book shows experienced programmers how to build and deploy scalable machine learning and deep learning models using serverless architectures with Microsoft Azure. You’ll learn step-by-step how to code machine learning into your projects using Python and pre-trained models that include tools such as image recognition, speech recognition, and classification. You’ll also examine issues around deployment and continuous delivery including scaling, security, and monitoring. This book is divided into four parts: Cloud-based development: learn the basics of serverless computing with machine learning, functions as a service (FaaS), and the use of APIs Adding intelligence: create serverless applications using Azure Functions; learn how to use pre-built machine-learning and deep-learning models Deployment and continuous delivery: get up to speed with Azure Kubernetes Service, as well as Azure Security Center, and Azure Monitoring Application examples: deliver data at the edge, build conversational interfaces, and use convolutional neural networks for image classification
    Note: Online resource; Title from title page (viewed September 17, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492052319/?ar
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    What Is Augmented Analytics? (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (35 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: As your business tries to make sense of today’s staggering amount of structured and unstructured data, traditional analytics will take you only so far. The key to success over the next few years will depend on augmented analytics, a method that embeds machine learning and natural language processing (NLP) in the process. This report explains how augmented analytics can help you uncover hidden insights, predict results, and even prescribe solutions. Author Alice LaPlante provides best practices for deploying augmented analytics, along with real-world case studies that show you how to take full advantage of this method. IT professionals, business managers, and CFOs will learn ways to democratize data use among business users and executives, using a self-service model. The future belongs to those who can get more from their data. This report shows you how. Get a primer on the key components and learn how they work together Delve into the benefits of—and roadblocks to—adopting augmented analytics Learn how companies use this method in marketing, sales, finance, and human resources Examine case studies of companies including Accenture and Riverbed
    Note: Online resource; Title from title page (viewed October 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492058458/?ar
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    Web Performance as a Competitive Advantage (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: To the typical web user, speed doesn’t only mean performance. Users’ perception of your app or site’s speed is heavily influenced by their user experience. This infographic describes the various ways your organization can improve performance to have a leg up on the competition.
    Note: Online resource; Title from title page (viewed July 15, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492039921/?ar
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    The ethics of analytics (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 59 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: As more and more data is being collected, concerns are constantly being raised about what data is appropriate to collect and how (or if) it should be analyzed. There are many ethical, privacy, and legal issues to consider, and no clear standards exist in many cases as to what is fair and what is foul. This means that organizations must consider their own principles and risk tolerance in order to implement the right policies. Bill Franks (International Institute For Analytics) explores a range of ethical, privacy, and legal issues that surround analytics today, framing the big questions to consider and detailing some of the trade-offs and ambiguities that must be addressed to answer them. This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    The Care and Feeding of Data Scientists (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (54 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: As a discipline, data science is relatively young, but the job of managing data scientists is younger still. Many people undertake this management position without the tools, mentorship, or role models they need to do it well. This report examines the steps necessary to build, manage, sustain, and retain a growing data science team. You’ll learn how data science management is similar to but distinct from other management types. Michelangelo D’Agostino, VP of Data Science and Engineering at ShopRunner, and Katie Malone, Director of Data Science at Civis Analytics, provide concrete tips for balancing and structuring a data science team. The authors provide tips for balancing and structuring a data science team, recruiting and interviewing the best candidates, and keeping them productive and happy once they're in place. In this report, you'll: Explore data scientist archetypes, such as operations and research, that fit your organization Devise a plan to recruit, interview, and hire members for your data science team Retain your hires by providing challenging work and learning opportunities Explore Agile and OKR methodology to determine how your team will work together Provide your team with a career ladder through guidance and mentorship
    Note: Online resource; Title from title page (viewed June 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492053972/?ar
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    Taking graph applications to production (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 41 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Over the past decade, Denise Gosnell (DataStax) has helped build some of the largest production applications of graph databases around the world. From those experiences, she’s collected a set of common areas in which teams frequently misstep when getting started with graph technology. It also happens that those themes parallel the experience of playing one of her favorite games, SimCity 2000. Denise walks you through a few of these topics. Know the rules. The introduction of graph data into your application introduces a new paradigm of data modeling: relationship-first design instead of entity-first design. The transition to relationship-first design principles introduces a new set of rules to consider for understanding your application’s performance, just like learning the rules of building a successful metropolis in SimCity . In this section, you’ll dive into the computational overhead introduced into your system from the branching factor and selectivity of your graph traversals. Things can quickly become catastrophic. Relationship-first data modeling can create a sleeping time bomb in your graph data: namely, supernodes. Just like in SimCity , high volumes of progress without proper planning will eventually introduce a catastrophe. To plan for this, you will need to track, mitigate, and eliminate the potential for supernodes within your applications. In this section, Denise introduces supernodes and presents tangible plans for avoiding the disasters which they can create. You’re going to make mistakes. Just like the learning process for understanding the tools and rules for building a successful city, you’ll inevitably make some mistakes when starting down the path of integrating graph technology into your stack. These common mistakes often start out as red herrings that are misinterpreted as graph problems. In this section, you’ll explore three use cases that are frequently misinterpreted as graph problems and learn techniques for avoiding these traps. This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    Streaming Data (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (33 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Managers and staff responsible for planning, hiring, and allocating resources need to understand how streaming data can fundamentally change their organizations. Companies everywhere are disrupting business, government, and society by using data and analytics to shape their business. Even if you don’t have deep knowledge of programming or digital technology, this high-level introduction brings data streaming into focus. You won’t find math or programming details here, or recommendations for particular tools in this rapidly evolving space. But you will explore the decision-making technologies and practices that organizations need to process streaming data and respond to fast-changing events. By describing the principles and activities behind this new phenomenon, author Andy Oram shows you how streaming data provides hidden gems of information that can transform the way your business works. Learn where streaming data comes from and how companies put it to work Follow a simple data processing project from ingesting and analyzing data to presenting results Explore how (and why) big data processing tools have evolved from MapReduce to Kubernetes Understand why streaming data is particularly useful for machine learning projects Learn how containers, microservices, and cloud computing led to continuous integration and DevOps
    Note: Online resource; Title from title page (viewed June 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492038085/?ar
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    Strata Data Conference 2019 - San Francisco, California (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 122 hr., 4 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Thousands of the data scientists, analysts, engineers, developers, and executives converged at the Strata Data Conference San Francisco in March 2019 to absorb the insights and wisdom of the data world's best minds. The conference featured more than 300 speakers, 10 keynotes, 10 tutorials, and 150+ technical sessions. This video compilation captures the best from the conference, offering more than 100 hours of material to review at your own pace. Highlights include: The Strata Business Summit - speakers, executive briefings, and tech sessions laser focused on a central theme: How do the world’s leading companies build their successful data strategies? Learn about recommendation engines, AI-based personalization solutions, data governance, ML based customer insight harvesting, and more from data wizards like Zachery Anderson (Electronic Arts), Eric Bradlow (The Wharton School), David Talby (Pacific AI), Paco Nathan (derwen.ai), Jonathan Francis (Starbucks), and JoLynn Lavin (General Mills). The Strata Data Ethics Summit – Is your AI really making good decisions or have you built a deceptive black box that reinforces ugly stereotypes? Alistair Croll (Strata Chair), Tim O'Reilly (O'Reilly Media), and Susan Etlinger's (Altimeter Group) eight hour deep dive into the thorny issues of data and algorithms with help from Jana Eggers (Nara Logics), Rumman Chowdhury (Accenture), Kathy Baxter (Salesforce), Carole Piovesan (McCarthy Tétrault), and more. Hours of tutorials from the world's top data engineers, such as Francesca Lazzeri (Microsoft) and Holden Karau (Google) on training and deploying models with Kubeflow across different cloud vendors; Dean Wampler (Lightbend) on performing machine learning using Kafka-based streaming pipelines; and Jason Dai (Intel) on the Analytics Zoo, an analytics/AI platform that seamlessly unites Spark, TensorFlow, Keras, and BigDL programs into an integrated pipeline. Sessions devoted to Data Science, Machine Learning & AI, including Sharad Goel (Stanford University) on the challenges of "fair machine learning", which aims to ensure that decisions guided by algorithms are equitable; Kelley Rivoire (Stripe) on scaling machine learning using the Railyard API; Vinod Vaikuntanathan (MIT) on performing machine learning on encrypted data; and Jeremy Howard (platform.ai) on recent advances in deep learning that allow non-engineers to train neural networks from scratch without needing code or pre-existing labels. Sessions focus...
    Note: Online resource; Title from title screen (viewed March 27, 2019)
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    Spotlight on Learning from Failure : Stablecoin Derisks The Blockchain Landscape with Wayne Chang (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 55 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Stablecoins—cryptocurrencies designed to avoid volatility—have been tried various times in the past with little to no success. Today, they're seeing a resurgence, as multiple firms work to develop their own stablecoins in an effort to solve the volatility crisis in cryptocurrency. Although nascent, these deployments have seen a wide amount of traction with both trading and application. But does the increased interest in stablecoins actually assuage the volatility crisis, and what does it mean for the future of blockchain-enabled businesses? In this edition of Spotlight on Learning from Failure , find out how stablecoins work, what opportunities and risks they present, and what to expect in the future with regard to the greater blockchain landscape. Wayne Chang will explain the history of stablecoins, how they solve for volatility issues in businesses and applications, and how they’ve been implemented over time. Wayne will also discuss the trade-offs between different stablecoins and how they fit into existing business models in order to drive value. Recorded on May 28, 2019. See the original event page for resources for further learning. Find future live events to attend or watch recordings of other past events . O’Reilly Spotlight explores emerging business and technology topics and ideas through a series of one-hour interactive events. In live conversations, participants share their questions and ideas while hearing the experts’ unique perspectives, insights, fears, and predictions for the future. In every edition of Spotlight on Learning from Failure , you’ll discover the lessons learned from failures both large and small. You’ll discover how successful companies have addressed setbacks, missteps, and challenges and how you can grow from their examples.
    Note: Online resource; Title from title screen (viewed October 4, 2019)
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    Spotlight on Innovation : AI Trends with Roger Chen (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 59 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Artificial intelligence can be intimidating. There are complex, sticky challenges of data collection and verification, algorithms and bias, and deploying AI services to production, plus ever-expanding ethical concerns. New trends in hardware, algorithms, tools, and data ecosystems are quickly transforming AI into a must-have for today’s organizations. Progress is accelerating, but so are obstacles; a successful, real-world implementation of AI depends on balancing many interdependent concerns. Recorded on March 13, 2019. See the original event page for resources for further learning. Find future live events to attend or watch recordings of other past events . O’Reilly Spotlight explores emerging business and technology topics and ideas through a series of one-hour interactive events. In live conversations, participants share their questions and ideas while hearing the experts’ unique perspectives, insights, fears, and predictions for the future. In every edition of Spotlight on Innovation , you’ll discover what successful companies have in common and how you can follow their lead with small practical steps to transform your organization and prepare for the Next Economy.
    Note: Online resource; Title from title screen (viewed August 1, 2019)
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    Spotlight on Data : Improving Uber’s Customer Support with Natural Language Processing and Deep Learning with Piero Molino (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 57 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: For a company looking to provide delightful user experiences, it's critical to resolve customer issues quickly and efficiently. Uber has implemented COTA, a system that helps representatives provide the best experience to customers by suggesting the best solutions. COTA improves the speed and reliability of customer support through automated ticket classification and answer selection for support representatives. By improving speed and reliability, COTA also helps reduce customer support operations costs. In this Spotlight on Data , find out how Uber leverages large-scale data and deep learning models for operational efficiency and improved user experience. Piero Molino details how Uber has reduced issue resolution time by 20% while maintaining levels of customer satisfaction, using NLP, deep learning, A/B testing, and productionized models. Recorded on July 2, 2019. See the original event page for resources for further learning. Find future live events to attend or watch recordings of other past events . O’Reilly Spotlight explores emerging business and technology topics and ideas through a series of one-hour interactive events. In live conversations, participants share their questions and ideas while hearing the experts’ unique perspectives, insights, fears, and predictions for the future. In every edition of Spotlight on Data , you’ll learn about, discuss, and debate the tools, techniques, questions, and quandaries in the world of data. You’ll discover how successful companies leverage data effectively and how you can follow their lead to transform your organization and prepare for the Next Economy.
    Note: Online resource; Title from title screen (viewed October 17, 2019)
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    Spotlight on Cloud : Reducing the Impact of Service Outages with Generic Mitigations with Jennifer Mace (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 59 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: While a mitigation is any action you might take to reduce the impact of a breakage—such as SSHing into an instance and clearing the cache or switching off machines to close down a vulnerability—generic mitigations are actions that first responders can take even before the root cause is fully understood. As such, they’re useful for addressing a wide variety of outages. Every service should employ at least one or two generic mitigations to minimize outage impacts. In this Spotlight on Cloud , Jennifer Mace, site reliability engineer at Google, shows you how to distinguish between specific and generic mitigations and how to identify what generic mitigations your service might need. Recorded on September 25, 2019. See the original event page for resources for further learning. Find future live events to attend or watch recordings of other past events . O’Reilly Spotlight explores emerging business and technology topics and ideas through a series of one-hour interactive events. In live conversations, participants share their questions and ideas while hearing the experts’ unique perspectives, insights, fears, and predictions for the future. In every edition of Spotlight on Cloud , you’ll learn about the complex, ever-evolving world of the cloud. You’ll discover how successful companies have adopted and embraced this massive network of shared information and how you can follow their lead to transform your organization and prepare for the Next Economy.
    Note: Online resource; Title from title screen (viewed October 21, 2019)
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    Responsible microservices (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 27 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: These days, you can’t swing a dry-erase marker without hitting someone talking about microservices. Developers are studying Eric Evans’s prescient book Domain-Driven Design . Teams are refactoring monolithic apps, looking for bounded contexts, and defining a ubiquitous language. And while there have been countless articles, videos, and talks to help you convert to microservices, few have spent any appreciable time asking if a given application should be a microservice. Nathaniel Schutta (Pivotal) shows you a set of factors you can apply to help you decide if something deserves to be a microservice or not. You’ll also look at what you need to do to maintain a healthy micro(services)biome. This session was recorded at the 2019 O'Reilly Software Architecture Conference in San Jose.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    Recommendation engines and mobile gaming (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 41 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Mobile gaming is a $50+ billion industry. Much of the industry’s growth has been fueled by the sale of in-game virtual resources and items to help players progress further or improve their overall gaming experience. One of the biggest concerns for mobile gaming developers is improving their overall monetization without getting in the way of players enjoying the game. KIXEYE—a developer of complex mobile strategy games—periodically provides its player base with a handful of in-app purchase options that provide different in-game content at different price points and discounts. The problem that companies run into using this model is what in-app purchases should be shown and when in order to maximize the number of in-app purchases. This is made more difficult at KIXEYE due to the massive number of in-app purchases available in the company’s games. So how do you solve this problem? Bysshe Easton and Thomas Dobbs explain how KIXEYE used hybrid recommendation engine techniques to create personalized in-app purchase recommendations for its customers, resulting in a 20%+ lift in user revenue. Along the way, they cover some parallelization techniques the company used to nearly eliminate scaling issues. This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    Real-time analytics at Uber : Bring SQL into everything (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 40 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: From determining the most convenient rider pickup points to predicting the fastest routes, Uber uses data-driven analytics to create seamless trip experiences. Uber’s analysts and engineers wanted to run real-time analytics with deep learning models. But copying data from one source to another is pretty expensive. Zhenxiao Luo explains how Uber supports real-time analytics with deep learning on the fly, without any data copying. He starts with the company’s big data infrastructure, specifically Hadoop, Spark, and Presto, and discusses how Uber uses Presto as an interactive SQL engine and deployed Hadoop Distributed File System, Pinot, MySQL, and Elasticsearch as storage solutions. He then details how Uber built a Presto Elasticsearch connector from scratch to support real-time analytics on heterogeneous data. He concludes by sharing the company’s production experience and roadmap. This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    Real-World Software Development (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (190 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: With Early Release ebooks, you get books in their earliest form—the author's raw and unedited content as he or she writes—so you can take advantage of these technologies long before the official release of these titles. Explore the latest Java-based software development techniques and methodologies through the project-based approach in this practical guide. Unlike books that use abstract examples and lots of theory, Real-World Software Development shows you how to develop several relevant projects while learning best practices along the way. With this engaging approach, junior developers capable of writing basic Java code will learn about state-of-the-art software development practices for building modern, robust and maintainable Java software. You’ll work with many different software development topics that are often excluded from software develop how-to references. Featuring real-world examples, this book teaches you techniques and methodologies for functional programming, automated testing, security, architecture, and distributed systems.
    Note: Online resource; Title from title page (viewed December 9, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781491967164/?ar
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    O'Reilly Artificial Intelligence Conference 2019 - San Jose, California (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 91 hr., 19 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: The O’Reilly Artificial Intelligence Conference San Jose 2019 was some of the world’s top AI practitioners sharing their AI passion and AI knowledge with thousands of attendees. It was Uber AI Lab’s Kenneth Stanley illuminating the future of AI with his talk about open-endedness learning. It was Danny Lange (Unity Technologies) on game environments that test the capabilities of AI-trained agents; Yi Zhang (University of California, Santa Cruz) on chatbots and the nearness of true conversational computing; and Hagay Lupesko (Facebook) on the challenges of mega-scale, deep learning-based personalization modeling. In short, AI San Jose 2019 was a mind-blower and this video compilation gives you access to virtually all of it with hours of material to peruse, study, and absorb on your own schedule. Highlights include: Complete video recordings of the best of AI San Jose 2019’s keynote addresses, deep dive tutorials, and technical sessions. Keynote addresses from AI thought leaders such as Andrew Feldman (Cerebras Systems), Sahika Genc (AWS DeepRacer/SageMaker RL), and Mike Jordan (UC Berkeley). Unrestricted access to the exclusive AI Business Summit’s executive briefings, best practice sessions, and tutorials led by AI business pros such as Michael Radwin (Intuit), Bahman Bahmani (Rakuten), Mayukh Bhaowal (Salesforce Einstein), Yael Gozin (Pfizer), and James Manyika (McKinsey & Company). Deep dive tutorials, including Jason Dai (Intel) on building deep learning apps for big data with the Analytics Zoo AI platform; Chaoran Yu (Lightbend) on doing machine learning (ML) with Kafka-based streaming pipelines; and Justina Petraityte (Rasa) on developing intelligent AI assistants based entirely on ML with open source Rasa NLU and Rasa Core. Sessions devoted to AI Implementation, such as Anuradha Gali (Uber) on using AI to leverage 15 million trips a day on the Uber platform; Roshan Sumbaly (Facebook) on connecting the dots between the software engineering and ML development worlds; Paige Bailey’s (Google) on TensorFlow 2.0's new features; and Alex Ratner (Snorkel) on building and managing training datasets for ML with open source Snorkel. Sessions focused on AI Models & Methods, including Lukas Biewald (Weights & Biases) review of how to use Keras to classify text with LSTMs and other ML techniques; and Francesca Lazzeri (Microsoft) on using AutoML to automate ML model selection and hyperparameter tuning. Dozens of how-to-do-it sessions detailing the tec...
    Note: Online resource; Title from title screen (viewed September 11, 2019)
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    Observability for developers : How to get from here to there (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 33 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: There’s been a lot of talk about software ownership—but what does “owning code in production” really mean for developers day to day? Many development teams still reach for logs in production as the most familiar way to bridge the development environment with production. Christine Yen (Honeycomb) makes the case that observability—and the skills to craft the right graphs and read them—benefits developers more than it does operators by examining several instances where well-informed devs can supercharge their development process, such as data-driven product decisions (or how to know more about what needs to be done than your PM), rewrites and migrations, feature flags and testing in production, and fine-grained performance analysis. Then, she lays out a series of steps to get your team from grepping unstructured text logs to outputting and analyzing well-structured traces. Instrumentation and observability aren’t all-or-nothing endeavors, and you’ll leave with an idea of the next step you can take to improve your ability to understand your production systems. This session was recorded at the 2019 O'Reilly Velocity Conference in San Jose.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    NLP from scratch : Solving the cold start problem for natural language processing (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 43 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Unstructured data in the form of documents, web pages, and social media interactions is an ever-growing, ever-more valuable data source for addressing present business problems, from exploring brand sentiment to identifying sensitive information in internal documents. Unfortunately, the classification and annotation algorithms behind solving these problems often require significant amounts of labeled training data to produce desired accuracy. Michael Johnson and Norris Heintzelman (Lockheed Martin) share several techniques they’ve implemented to build classification and NER models from scratch. They lead a tour through this space as it applies to NLP and demonstrate their approach and architecture for the following techniques: Weak supervision for news documents: Using rules base classification alongside deep learning system for text classification Active learning and human in the loop: Explaining how breakthroughs in transfer learning for NLP have impacted their active learning framework for building an LSTM-based relevance model Creative training sets: Identifying and cleaning already-labeled datasets, training classifier on “only” positive examples NER adjudication: Combining knowledge from several annotation sources that leverages the strengths of each source For each of these topics, Michael and Norris outline the theoretical foundation, the implementation architecture, and tools used and discuss the problems they encountered—so you can avoid making the same mistakes.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    Monolith to Microservices (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    ISBN: 9781492047810 , 1492047813 , 9781492047797 , 1492047791
    Language: English
    Pages: 1 online resource (284 pages)
    Edition: 1st edition
    Parallel Title: Erscheint auch als
    DDC: 005.1
    Keywords: Application software Development ; Computer architecture ; Distributed operating systems (Computers) ; Computer software Development ; Software patterns ; Electronic books ; local ; Logiciels d'application ; Développement ; Ordinateurs ; Architecture ; Systèmes d'exploitation répartis ; Logiciels ; Modèles de conception ; Application software ; Development ; Computer architecture ; Computer software ; Development ; Distributed operating systems (Computers) ; Software patterns
    Abstract: How do you detangle a monolithic system and migrate it to a microservices architecture? How do you do it while maintaining business-as-usual? As a companion to Sam Newman’s extremely popular Building Microservices , this new book details a proven method for transitioning an existing monolithic system to a microservice architecture. With many illustrative examples, insightful migration patterns, and a bevy of practical advice to transition your monolith enterprise into a microservice operation, this practical guide covers multiple scenarios and strategies for a successful migration, from initial planning all the way through application and database decomposition. You’ll learn several tried and tested patterns and techniques that you can use as you migrate your existing architecture. Ideal for organizations looking to transition to microservices, rather than rebuild Helps companies determine whether to migrate, when to migrate, and where to begin Addresses communication, integration, and the migration of legacy systems Discusses multiple migration patterns and where they apply Provides database migration examples, along with synchronization strategies Explores application decomposition, including several architectural refactoring patterns Delves into details of database decomposition, including the impact of breaking referential and transactional integrity, new failure modes, and more
    Note: Online resource; Title from title page (viewed November 25, 2019)
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    ML at Twitter : A deep dive into Twitter's timeline (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 41 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Machine learning has allowed Twitter to drive engagement, promote healthier conversations, and deliver catered advertisements. Cibele Montez Halasz and Satanjeev Banerjee describe one of those use cases: timeline ranking. They share some of the optimizations that the team has made—from modeling to infrastructure—in order to have models that are both expressive and efficient. You’ll explore the feature pipeline, modeling decisions, platform improvements, hyperparameter tuning, and architecture (alongside discretization and isotonic calibration) as well as some of the challenges Twitter faced by working with heavily text-based (sparse) data and some of the improvements the team made in its TensorFlow-based platform to deal with these use cases. Join in to gain a holistic view of one of Twitter’s most prominent machine learning use cases. This session was recorded at the 2019 O'Reilly Artificial Intelligence Conference in New York.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    Mining the Social Web, 3rd Edition (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (432 pages)
    Edition: 3rd edition
    Keywords: Electronic books ; local
    Abstract: Mine the rich data tucked away in popular social websites such as Twitter, Facebook, LinkedIn, and Instagram. With the third edition of this popular guide, data scientists, analysts, and programmers will learn how to glean insights from social media—including who’s connecting with whom, what they’re talking about, and where they’re located—using Python code examples, Jupyter notebooks, or Docker containers. In part one, each standalone chapter focuses on one aspect of the social landscape, including each of the major social sites, as well as web pages, blogs and feeds, mailboxes, GitHub, and a newly added chapter covering Instagram. Part two provides a cookbook with two dozen bite-size recipes for solving particular issues with Twitter. Get a straightforward synopsis of the social web landscape Use Docker to easily run each chapter’s example code, packaged as a Jupyter notebook Adapt and contribute to the code’s open source GitHub repository Learn how to employ best-in-class Python 3 tools to slice and dice the data you collect Apply advanced mining techniques such as TFIDF, cosine similarity, collocation analysis, clique detection, and image recognition Build beautiful data visualizations with Python and JavaScript toolkits
    Note: Online resource; Title from title page (viewed January 2, 2019)
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    Machine Learning Pocket Reference (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (318 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project. Ideal for programmers, data scientists, and AI engineers, this book includes an overview of the machine learning process and walks you through classification with structured data. You’ll also learn methods for clustering, predicting a continuous value (regression), and reducing dimensionality, among other topics. This pocket reference includes sections that cover: Classification, using the Titanic dataset Cleaning data and dealing with missing data Exploratory data analysis Common preprocessing steps using sample data Selecting features useful to the model Model selection Metrics and classification evaluation Regression examples using k-nearest neighbor, decision trees, boosting, and more Metrics for regression evaluation Clustering Dimensionality reduction Scikit-learn pipelines
    Note: Online resource; Title from title page (viewed August 29, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492047537/?ar
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    Kotlin Cookbook (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (204 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Kotlin is the fastest-growing "alternative" language on the JVM, and its use is becoming pervasive in Android, native applications, and other areas. Other books on Kotlin teach the language in the traditional manner. The appeal of a cookbook is that it lets you find exactly the techniques you need exactly when you need them. This book will be a daily reference for existing Kotlin developers and those programmers learning to apply the language to new areas.
    Note: Online resource; Title from title page (viewed November 5, 2019)
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    How to build privacy and security into deep learning models (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 38 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: In recent years, we’ve seen tremendous improvements in artificial intelligence, due to the advances of neural-based models. However, the more popular these algorithms and techniques get, the more serious the consequences of data and user privacy. These issues will drastically impact the future of AI research—specifically how neural-based models are developed, deployed, and evaluated. Yishay Carmiel (IntelligentWire) shares techniques and explains how data privacy will impact machine learning development and how future training and inference will be affected. Yishay first dives into why training on private data should be addressed, federated learning, and differential privacy. He then discusses why inference on private data should be addressed, homomorphic encryption and neural networks, a polynomial approximation of neural networks, protecting data in neural networks, data reconstruction from neural networks, and methods and techniques to secure data reconstruction from neural networks. This session was recorded at the 2019 O'Reilly Artificial Intelligence Conference in New York.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    Having the bubble : How your experts build, maintain, and spread deep system knowledge (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 34 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: We fret about how to break system knowledge out of knowledge silos—the expert individuals with a deep intuitive understanding of our complex systems. How do these people engage with the system and act to protect, fortify, and improve it? How can engineering organizations protect and fortify experts as a key part of their observability strategy? Beth Long (New Relic) explains how those experts represent both a vulnerability and a strength and why understanding them as a key mechanism in your larger systems helps you harness their power and protect against fragility. This session was recorded at the 2019 O'Reilly Velocity Conference in San Jose.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    Hands-On Smart Contract Development with Solidity and Ethereum (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (270 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Learn how to design, develop, and deploy smart contracts on the Ethereum blockchain. With this practical book, software developers with a high-level understanding of the blockchain will use the Solidity programming language to write decentralized applications (dApps) using the web3.js library. Smart contracts have allowed technologists to create a new breed of software systems that have ushered in the next revolution in human organization. Kevin Solorio, Randall Kanna, and David Hoover teach you the fundamentals of Solidity, as well as key topics such as unit testing, deployment, and preventing security vulnerabilities. You'll also learn how to leverage the built-in public/private key cryptography in the Ethereum protocol. Learn the fundamentals of how the Ethereum blockchain works Setup a local Ethereum client using Parity Develop and test secure smart contracts using Solidity and Vyper Learn how to deploy smart contracts Interact with your smart contract using Web3 (JavaScript) Work with hands-on examples and walkthroughs of common scenarios
    Note: Online resource; Title from title page (viewed December 2, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492045250/?ar
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    Getting Started with Enterprise Blockchain (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (84 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Blockchains have many uses beyond cryptocurrencies such as Bitcoin. These shared, distributed ledgers also enable businesses to record transactions between parties in an efficient, verifiable, and permanent manner—unlike traditional methods. Using a blockchain in business can still pose numerous challenges, however. This ebook explains how developers can establish a blockchain network to handle business-to-business transactions while maintaining privacy and confidentiality. Members of IBM’s global blockchain team show you how to start using these open, distributed ledgers to add value to your business networks. Unlike simple ledgers and contracts, blockchains offer irrefutable proof that all parties involved in a transaction agree to the details—creating a source of truth that today’s conventional business-to-business systems lack. You’ll learn: How blockchains for business provide a shared, distributed ledger with smart contracts How to identify and implement the scenarios for which blockchain is most suited What developers need to know about enterprise blockchain The important design and architectural considerations when building a blockchain-based platform How chaincode encapsulates business logic to define assets and the terms of transactions How to implement a blockchain application based on a commercial paper case study What the future holds for blockchain
    Note: Online resource; Title from title page (viewed July 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492052715/?ar
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    From flat files to deconstructed databases : The evolution and future of the big data ecosystem (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 44 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Over the past 10 years, big data infrastructure has evolved from flat files in a distributed filesystem to an efficient ecosystem to a fully deconstructed and open source database with reusable components. With Hadoop, we started from a system that was good at looking for a needle in a haystack using snowplows. We had a lot of horsepower and scalability but lacked the subtlety and efficiency of relational databases. But since Hadoop provided the ultimate flexibility compared to the more constrained and rigid RDBMSs, we didn’t mind and plowed through. However, machine learning, recommendations, matching, abuse detection, and data-driven products in general require a more flexible infrastructure. Over time, we started applying everything that had been known to the database world for decades to this new environment. We’d been told loud enough how Hadoop was a huge step backward. And it was true to some degree. The key difference was the flexibility of the Hadoop stack. There are many highly integrated components in a relational database and decoupling them took some time. Today, we see the emergence of key components, such as optimizers, columnar storage, in-memory representation, table abstraction, and batch and streaming execution, as standards that provide the glue between the options available to process, analyze, and learn from our data. We’ve been deconstructing the tightly integrated relational database into flexible reusable open source components. Storage, compute, multitenancy, and batch or streaming execution are all decoupled and can be modified independently to fit every use case. Julien Le Dem (WeWork) discusses the key open source components of the big data ecosystem—including Apache Calcite, Parquet, Arrow, Avro, and Kafka as well as batch and streaming systems—and explains how they relate to each other and how they make the ecosystem more of a database and less of a filesystem. (Parquet is the columnar data layout to optimize data at rest for querying. Arrow is the in-memory representation for maximum throughput execution and overhead-free data exchange. Calcite is the optimizer to make the most of our infrastructure capabilities.) Julien also explores the emerging components that are still missing or haven’t become standard yet to fully materialize the transformation to an extremely flexible database that lets you innovate with your data. This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    Expert Playlist Intro : Lessons from Amazon, Google, Apple and Other Silicon Valley Giants (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 4 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: In this brief introduction to Tim O'Reilly's Expert Playlist , find out why he selected these pieces to study how some of the most advanced companies on the planet not only use technology but build their culture to support it.
    Note: Online resource; Title from title screen (viewed August 25, 2019)
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    Escaping the Build Trap (Audio Book) (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (20778 pages)
    Edition: 1st edition
    Keywords: Audiobooks ; local
    Abstract: This audio book is for Product Managers of all levels (including the VP level) who understand that if companies want to remain innovative in today’s market, they have to adopt a culture of learning and customer-centric practices that are focused on outcomes over outputs. This audio book provides Product Managers with a practical process and a toolbox of product management principles that can be applied to any company, big or small, and will help them produce real positive results. They will learn how to overcome product development roadblocks, the secrets to communicating and collaborating within a company structure, and how to build products that benefit both the business and the customer.
    Note: Online resource; Title from title page (viewed April 15, 2019)
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    Digital Transformation Game Plan (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (361 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: The Digital Age is having a broad and profound impact on companies and entire industries. Rather than simply automate or embed digital technology into existing offerings, your business needs to rethink everything. In this practical book, three ThoughtWorks professionals provide a game plan to help your business through this transformation, along with technical concepts that you need to know to be an effective leader in a modern digital business. Chock-full of practical advice and case studies that show how businesses have transitioned, this book reveals lessons learned in guiding companies through digital transformation. While there’s no silver bullet available, you’ll discover effective ways to create lasting change at your organization. With this book, you’ll discover how to: Realign the business and operating architecture to focus on customer value Build a more responsive and agile organization to deal with speed and ambiguity Build next generation technology capability as a core differentiator
    Note: Online resource; Title from title page (viewed October 30, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492054382/?ar
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    DevOps and Business (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (77 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: DevOps is much more than a set of practices to eliminate silos between development and operations groups. If your company’s DevOps transformation is to succeed, you need to blur the lines between business and technology domains. This report helps engineering leaders understand what drives the business and provides best practices for aligning technology with business goals to increase efficiency and improve the bottom line. Author Leon Fayer, vice president of software development at Teaching Strategies, provides methods and techniques to help your organization improve cross-departmental processes, cooperation, and visibility. Getting IT and business groups to adopt DevOps principles will go a long way toward accomplishing that goal. This report shows you how. Use practical strategies to teach stakeholders how DevOps can provide value for the business Quantify the ROI value of DevOps implementation and culture changes Determine the best ways to position technology groups to support business outcomes Improve communication efficiency to identify mistakes and optimize service delivery Understand the importance of continuous insight into business performance Build empathy and trust by encouraging people to support common goals and solve problems together
    Note: Online resource; Title from title page (viewed July 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492036609/?ar
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    Deep learning for recommender systems, or how to compare pears with apples (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 42 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Recommender systems support the decision making processes of customers with personalized suggestions. These widely used systems influence the daily life of almost everyone across domains like ecommerce, social media, and entertainment. However, the efficient generation of relevant recommendations in large-scale systems is a very complex task. In order to provide personalization, engines and algorithms need to capture users’ varying tastes and find mostly nonlinear dependencies between them and a multitude of items. Enormous data sparsity and ambitious real-time requirements further complicate this challenge. At the same time, deep learning has been proven to solve complex tasks like object or speech recognition where traditional machine learning failed or showed mediocre performance. Join Marcel Kurovski (inovex) to explore a use case for vehicle recommendations at mobile.de, Germany’s biggest online vehicle market. Marcel shares a novel regularization technique for the optimization criterion and evaluates it against various baselines. To achieve high scalability, he combines this method with strategies for efficient candidate generation based on user and item embeddings—providing a holistic solution for candidate generation and ranking. The proposed approach outperforms collaborative filtering and hybrid collaborative-content-based filtering by 73% and 143% for MAP5. It also scales well for millions of items and users returning recommendations in tens of milliseconds. This session was recorded at the 2019 O'Reilly Artificial Intelligence Conference in New York.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    Data Warehousing with Greenplum, 2nd Edition (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (120 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local
    Abstract: Data professionals are confronting the most disruptive change since relational databases appeared in the 1980s. SQL is still a major tool for data analytics, but conventional relational database management systems can’t handle the increasing size and complexity of today’s datasets. This updated edition teaches you best practices for Greenplum Database, the open source massively parallel processing (MPP) database that accommodates large sets of nonrelational and relational data. Marshall Presser, field CTO at Pivotal, introduces Greenplum’s approach to data analytics and data-driven decisions, beginning with its shared-nothing architecture. IT managers, developers, data analysts, system architects, and data scientists will all gain from exploring data organization and storage, data loading, running queries, and learning to perform analytics in the database. Discover how MPP and Greenplum will help you go beyond the traditional data warehouse. This ebook covers: Greenplum features, use case examples, and techniques for optimizing use Four Greenplum deployment options to help you balance security, cost, and time to usability Why each networked node in Greenplum’s architecture includes an independent operating system, memory, and storage Additional tools for monitoring, managing, securing, and optimizing query responses in the Pivotal Greenplum commercial database
    Note: Online resource; Title from title page (viewed July 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492058137/?ar
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    Database migrations don't have to be painful, but the road will be bumpy (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 31 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Change is the only constant; upgrades are inevitable. Believe it or not, this also applies to your database. There are many drivers for such changes, such as technology stack updates and new data center or event cloud migrations. A database migration isn’t an easy task. Preparation and execution takes time and leaves no room for mistakes. And once you start, there’s no going back. But is this the only way? Adrian Lungu and Serban Teodorescu (Adobe) explain how—inspired by the green-blue deployment technique—the Adobe Audience Manager team developed an active-passive database migration procedure that allows them to test database clusters in production, minimizing the risks without compromising the innovation. It was successfully applied twice to upgrade the entire database technology stack—but it’s never a smooth move when your databases are 200-node Cassandra clusters with hundreds of terabytes of data and downtime is not an option. The first migration was focused only on software upgrades. For the second upgrade, the team’s confidence was so high that they added a twist: a couple of more changes besides the Cassandra version—AWS instance type, operating system, disk settings, memory settings, JVM, and a few more. What could go wrong? Well. . .everything. Adrian and Serban describe the migration technique and present an extensible database client that makes all the active-passive management possible with just a configuration change. Yes, you heard it right. No code changes, just configurations. They then share a series of tales and lessons learned during the migration of over 500 Cassandra nodes. Most of the lessons aren’t Cassandra related but instead apply to hardware, drivers, operating system, or the JVM—debugging for days and searching for that metric anomaly or that log line that would give us a hint on what went wrong. Join in to see how you can avoid some of these pitfalls in your own projects. This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    Choreographing microservices (San Jose, CA) (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 26 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Choreographed microservices talk to each other asynchronously, blindly broadcasting notifications into a service cloud. Those notifications are handled by whatever client services are interested. These systems eliminate many of the problems associated with orchestrated systems (which work more like synchronous function calls) and are typically much faster than orchestrated systems, but they have their own idiosyncrasies and implementation challenges. Allen Holub explores the inherent problems in orchestrated systems and then looks at how choreography can solve those problems. Allen explores three approaches to choreography: HTTP based, pub/sub messaging based, and brokerless swarming systems. He introduces appropriate messaging architectures and frameworks and looks at several practical examples. Finally, Allen looks at event storming: one of the best approaches to designing choreographed systems. You’ll leave with an understanding of both why you should be using choreography for most high-level APIs and how to design and build these systems. This session was recorded at the 2019 O'Reilly Software Architecture Conference in San Jose.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    Building Web Apps with WordPress, 2nd Edition (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (531 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local
    Abstract: WordPress is much more than a blogging platform. As this practical guide clearly demonstrates, you can use WordPress to build web apps of any type—not mere content sites, but full-blown apps for specific tasks. If you have PHP experience with a smattering of HTML, CSS, and JavaScript, you’ll learn how to use WordPress plugins and themes to develop fast, scalable, and secure web apps, native mobile apps, web services, and even a network of multiple WordPress sites. In the book's updated second edition, the authors use examples from their recently released SchoolPress app to explain concepts and techniques throughout the book. All code examples are available on GitHub. Compare WordPress with traditional app development frameworks Use themes for views, and plugins for backend functionality Get suggestions for choosing WordPress plugins—or build your own Manage user accounts and roles, and access user data Build asynchronous behaviors in your app with jQuery Develop native apps for iOS and Android, using wrappers Incorporate PHP libraries, external APIs, and web service plugins Collect payments through ecommerce and membership plugins Use techniques to speed up and scale your WordPress app With Early Release ebooks, you get books in their earliest form—the author’s raw and unedited content as he or she writes—so you can take advantage of these technologies long before the official release of these titles.
    Note: Online resource; Title from title page (viewed December 18, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781491990070/?ar
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    Blockchain as a Service (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (69 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: While the merits of cryptocurrency continue to be debated, the underlying technology—the blockchain—can be applied in many other ways to solve problems that have plagued organizations for years. To spur adoption of blockchain for these newer use cases, many technology providers and leading businesses have begun offering cloud-based blockchain-as-a-service (BaaS) options. This report brings you up to speed on these emerging opportunities. Author Karen Kilroy helps technical business leaders, solutions architects, and innovation officers understand blockchain and evaluate options for BaaS. Through interviews with enterprise blockchain experts and practitioners, you’ll learn how this service model has evolved and what it offers. You’ll also examine the landscape of BaaS offerings, get a project started, and learn where the technology is going. You’ll learn: Why blockchain is different from a relational database or other distributed ledger technologies How blockchain is used in business applications The nuts and bolts of a blockchain network, including participants, assets, transactions, and smart contracts How to architect a typical BaaS application as a standalone multiuser application Current BaaS offerings and how to choose the one that’s right for you Five industry-changing use cases for BaaS, including international trade, identity verification, and royalties tracking Examples of how BaaS may be used in the future
    Note: Online resource; Title from title page (viewed November 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492073475/?ar
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    Asterisk : The Definitive Guide, 5th Edition (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (412 pages)
    Edition: 5th edition
    Keywords: Electronic books ; local
    Abstract: Design a complete Voice over IP (VoIP) or traditional PBX system with Asterisk, even if you have only basic telecommunications knowledge. This bestselling guide makes it easy with a detailed roadmap that shows you how to install and configure this open source software, whether you’re upgrading your existing phone system or starting from scratch. Ideal for Linux administrators, developers, and power users, this updated fifth edition shows you how to set up VoIP-based private telephone switching systems within the enterprise. You’ll get up to speed on the features in Asterisk 16, the latest long-term support release from Digium. This book also includes new chapters on WebRTC and the Asterisk Real-time Interface (ARI). Discover how WebRTC provides a new direction for Asterisk Gain the knowledge to build a simple but complete phone system Build an interactive dialplan, using best practices for Asterisk’s advanced features Learn how ARI has emerged as the API of choice for interfacing web development languages with Asterisk
    Note: Online resource; Title from title page (viewed June 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492031598/?ar
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    Artificial intelligence on human behavior : New insights into customer segmentation (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 35 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Brands, marketers, and product designers need to understand their customers. Traditionally, market research was driven by surveys and focus groups of limited scale. Today, digital signals like web browsing behavior can provide a stream of observed behavioral data that is rich with information about a user’s interests, needs, and preferences. This type of data, coupled with machine learning techniques, holds the promise of freeing market research from the constraints of self-reported customer data. In its raw state, web browsing data is both too detailed and too sparse to be comprehensible, let alone actionable. Melinda Han Williams (Dstillery) explores semantic embeddings as a novel approach for understanding observed digital consumer behavior and details how to use a semantic embedding of web browsing behavior to drive unsupervised clustering for customer segmentation. You’ll learn how Dstillery has trained a neural network on 15 billion behavioral interactions. The resulting model can be seen as a much lower dimensional embedding of the internet and, if projected into two or three dimensions, as an interactive map. This taxonomy of internet behavior can be used as the foundation for a number of applications, providing unparalleled insights into consumer behavior and needs. This session was recorded at the 2019 O'Reilly Strata Data Conference in San Francisco.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    Applying Deep Learning in Business (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (27 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: According to a recent poll conducted by O’Reilly Media, most data scientists already know what AI technologies, such as deep learning, can do. Now they want to learn how to implement neural networks and deep learning to address their unique business objective. They’re looking for business use cases, real-world examples, and tutorials and tips for overcoming challenges with these projects. And they’re seeking a Cloud-based service so they can spin up a service in matter of minutes and only pay for what they use. With tools such as Deep Learning as a Service within IBM Watson Studio, building and deploying deep learning models in the enterprise is getting easier. This practical report provides enterprise application developers with specific use cases and steps for implementation, data scientist Federico Castanedo provides readers with a foundational understanding of deep learning and demonstrates how companies are using it in their business today. You’ll learn two approaches to implementing deep learning in your organization: build and train your own deep learning models, or leverage pre-trained models. Learn what deep learning can do in the enterprise Understand the general process of building and training neural networks in-house for deep learning projects Contrast building your own solution with using and deploying pre-built models Design deep learning models in the cloud with IBM Watson Studio and popular frameworks such as TensorFlow, Caffe, PyTorch and Keras
    Note: Online resource; Title from title page (viewed October 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492039211/?ar
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    An Introduction to Machine Learning Interpretability, 2nd Edition (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (60 pages)
    Edition: 2nd edition
    Keywords: Electronic books ; local
    Abstract: Innovation and competition are driving analysts and data scientists toward increasingly complex predictive modeling and machine learning algorithms. This complexity makes these models accurate, but can also make their predictions difficult to understand. When accuracy outpaces interpretability, human trust suffers, affecting business adoption, model validation efforts, and regulatory oversight. In the updated edition of this ebook, Patrick Hall and Navdeep Gill from H2O.ai introduce the idea of machine learning interpretability and examine a set of machine learning techniques, algorithms, and models to help data scientists improve the accuracy of their predictive models while maintaining a high degree of interpretability. While some industries require model transparency, such as banking, insurance, and healthcare, machine learning practitioners in almost any vertical will likely benefit from incorporating the discussed interpretable models, and debugging, explanation, and fairness approaches into their workflow. This second edition discusses new, exact model explanation techniques, and de-emphasizes the trade-off between accuracy and interpretability. This edition also includes up-to-date information on cutting-edge interpretability techniques and new figures to illustrate the concepts of trust and understanding in machine learning models. Learn how machine learning and predictive modeling are applied in practice Understand social and commercial motivations for machine learning interpretability, fairness, accountability, and transparency Get a definition of interpretability and learn about the groups leading interpretability research Examine a taxonomy for classifying and describing interpretable machine learning approaches Gain familiarity with new and more traditional interpretable modeling approaches See numerous techniques for understanding and explaining models and predictions Read about methods to debug prediction errors, sociological bias, and security vulnerabilities in predictive models Get a feel for the techniques in action with code examples
    Note: Online resource; Title from title page (viewed October 25, 2019)
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    A Case Study in Community-Driven Software Adoption (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (38 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Many SRE tasks are the same across all types of software, yet individual teams often develop very different automation tools and processes and can resist standardization. Why does this diversity exist? And how can an organization prevent SRE teams from duplicating their development efforts while cutting down on their manual labor? This case study details how and why several teams at Google eventually gravitated to one tool—Sisyphus—despite its lack of managerial support, best practices, and high-quality code. Google engineer Richard Bondi examines how Sisyphus was able to proliferate across Google’s SRE teams. You’ll delve into data that demonstrates Sisyphus’s adoption success and learn how this tool overcame two significant challenges along the way. This case study offers site reliability engineers, managers, and organizational practitioners a clear example of how a tool influenced SRE behavior by adapting to SRE culture. You’ll explore ways to: Tailor tool development to the specifics of your organization's environment Design tools that are adaptable to individual SRE teams Accommodate teams and individuals who have traditionally been resistant to top-down mandates Decide when a tool is "good enough" rather than perfect
    Note: Online resource; Title from title page (viewed July 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781098114596/?ar
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    What Is SRE? (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (38 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Site Reliability Engineering is an outgrowth of the "always-on" world of online services. Initiated at Google more than a decade ago, SRE helps many of today’s sites run effectively and reliably, even as those sites continuously introduce new features. This ebook explains how site reliability engineers work with development teams to meet the fundamental customer expectation that online services can and must be reliable. Kurt Andersen from LinkedIn and Craig Sebenik from Split explain how new and existing organizations can successfully adopt SRE processes for managing—and learning from—a host of system incidents. Complete with case studies from Google, LinkedIn, and Slack, this ebook explores SRE and provides guiding principles for implementing the role in your organization. Understand how your company’s culture, capabilities, and organizational structure affect the way you approach SRE Learn how SREs strive to maintain system components in a resilient, predictable, consistent, repeatable, and measured state Examine differences between SRE and other operational roles, such as DevOps and classical ops Learn approaches for adopting SRE in either a new or existing organization Explore key patterns and anti-patterns for introducing SRE in your organization
    Note: Online resource; Title from title page (viewed June 25, 2019)
    URL: lizenzpflichtig
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  • 96
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    Strengthening Deep Neural Networks (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (244 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: As deep neural networks (DNNs) become increasingly common in real-world applications, the potential to deliberately "fool" them with data that wouldn’t trick a human presents a new attack vector. This practical book examines real-world scenarios where DNNs—the algorithms intrinsic to much of AI—are used daily to process image, audio, and video data. Author Katy Warr considers attack motivations, the risks posed by this adversarial input, and methods for increasing AI robustness to these attacks. If you’re a data scientist developing DNN algorithms, a security architect interested in how to make AI systems more resilient to attack, or someone fascinated by the differences between artificial and biological perception, this book is for you. Delve into DNNs and discover how they could be tricked by adversarial input Investigate methods used to generate adversarial input capable of fooling DNNs Explore real-world scenarios and model the adversarial threat Evaluate neural network robustness; learn methods to increase resilience of AI systems to adversarial data Examine some ways in which AI might become better at mimicking human perception in years to come
    Note: Online resource; Title from title page (viewed July 23, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492044949/?ar
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  • 97
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    Spotlight on Learning from Failure : Creating Better Data Pipelines with Natalino Busa (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 59 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: When considering the complexities of implementing a next-generation data pipeline, the risk of over-promising and under-delivering is incredibly high due to the overwhelming expectations placed on predictive analytics today. It’s critical to look at a number of factors—like your company’s culture and the historic promise gap between ETL (extract, transform, load) in the 1970s and AI (artificial intelligence) in the 2010s—to overcome the challenges and succeed. Natalino Busa discusses how to bust the myths, deconstruct the false assumptions, and avoid common pitfalls in order to build and deliver successful data pipelines that deliver real value to your organization. Recorded on February 26, 2019. See the original event page for resources for further learning. Find future live events to attend or watch recordings of other past events . O’Reilly Spotlight explores emerging business and technology topics and ideas through a series of one-hour interactive events. In live conversations, participants share their questions and ideas while hearing the experts’ unique perspectives, insights, fears, and predictions for the future. In every edition of Spotlight on Learning from Failure , you’ll discover the lessons learned from failures both large and small. You’ll discover how successful companies have addressed setbacks, missteps, and challenges and how you can grow from their examples.
    Note: Online resource; Title from title screen (viewed August 27, 2019)
    URL: lizenzpflichtig
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  • 98
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    What Is Domain-Driven Design? (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (96 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: The majority of software projects are delivered late or over budget, or they fail to meet the client’s requirements. Attack the problem head-on and build better software with domain-driven design (DDD)—a methodology that aligns software design with a business’s domain, needs, and strategy. In this report, Vladik Khononov introduces the key patterns and practices of domain-driven design and shows you how to apply them to improve the success rate of your projects. You’ll discover how to explore, analyze, and model your company’s business domain along with techniques for implementing that knowledge. Once you understand the fundamentals, you’ll be able to selectively apply DDD concepts to analyze and simplify your codebase, explore new requirements, and more. You’ll learn: Key domain-driven design concepts, including ubiquitous language and bounded contexts How to employ “event storming” to streamline the process of discovering domain knowledge and building a ubiquitous language Patterns and techniques for implementing business logic and architecting solutions that deliver business goals How to maintain and evolve both tactical and strategic designs over time
    Note: Online resource; Title from title page (viewed October 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492057802/?ar
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  • 99
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    What Are Miniservices? (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (26 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Miniservices provide a valuable middle ground between monoliths and microservices. As Nicholas Keune explains in this report, miniservices are suited for application landscapes involving data-intensive workloads that span monoliths and microservices or cross the traditional boundaries of a service context. Drawn from the work of many development teams, the report gives a model and language to data-centric system attributes so that they can be considered more proactively in the design discussion. Combining monolithic corporate or third-party systems with microservices requires a design pattern to balance both local and global aspects of the data lifecycle. The approach advocated here, called a data discourse , is both flexible and bounded by guiding principles that help bring data discussions into early architectural conversations. Using real-world experiences and use cases, the report focuses on three of the most commonly observed attributes in a miniservice: consistency, transactionality, and proximity. The examples illustrate how design discussions about data discourses lead to miniservice creation, and how miniservices help solve otherwise difficult architectural challenges. With this report, you’ll learn: What miniservices are and how they offer solutions to challenges What data discourses are and how to use them How data discourses and miniservices help shift design discussions around data
    Note: Online resource; Title from title page (viewed September 25, 2019)
    URL: https://learning.oreilly.com/library/view/-/9781492073505/?ar
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  • 100
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    Spotlight on Data : Creating Smart Products Requires Collaboration with Gretchen Anderson (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 55 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: We're experiencing a boom in smart products and services, from virtual assistants like Alexa to robotic surgical tools. But as we design and develop products of increasing complexity—incorporating machine learning to drive autonomous decision making—measuring output and outcomes also explodes in complexity. In the face of all this complexity, how do you design your teams and collaborative processes to ensure a successful product? Teams have to move away from merely seeking “approvals” and toward collaborating on the goals and parameters; they must also target use cases that will make or break the experience for end users. The more dynamic the technology, the wider the range of diverse perspectives that must inform the process. Data scientists, designers, developers, lawyers, and regulators all need to weigh in, and their voices need to be heard and accounted for. Recorded on April 15, 2019. See the original event page for resources for further learning. Find future live events to attend or watch recordings of other past events . O’Reilly Spotlight explores emerging business and technology topics and ideas through a series of one-hour interactive events. In live conversations, participants share their questions and ideas while hearing the experts’ unique perspectives, insights, fears, and predictions for the future. In every edition of Spotlight on Data , you’ll learn about, discuss, and debate the tools, techniques, questions, and quandaries in the world of data. You’ll discover how successful companies leverage data effectively and how you can follow their lead to transform your organization and prepare for the Next Economy.
    Note: Online resource; Title from title screen (viewed September 17, 2019)
    URL: lizenzpflichtig
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