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  • Safari, an O’Reilly Media Company  (376)
  • Salon, Data  (51)
  • Boston, MA : Safari  (427)
  • [Erscheinungsort nicht ermittelbar] : IBM Redbooks
  • Electronic videos ; local  (424)
  • Application software ; Development  (3)
Datasource
Material
Language
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Keywords
  • 1
    Online Resource
    Online Resource
    Real Time, Contextual and Personalized Recommendations (2020)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 30 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Dhivya Rajprasad, Data Scientist at Levi Strauss & Co Levi Strauss and Co has always been at the helm of innovation with their classic denims and seasonal takes on the future of denim . We would like to enable users who visit our website, receive our emails and visit our stores to have the most personalized experience with easier product discovery. To enable this, I have built recommendation systems based on live and past user behavior and with minimal infrastructure. The talk features two main areas: 1. How to work with minimal data, implicit feedback and business to build recommender systems that satisfy users needs while keeping in mind overarching business KPIs 2. How to use real stream of events and past indications to give a completely personalized experience that can keep updating based on user interaction with minimal architectural requirements.
    Note: Online resource; Title from title screen (viewed March 24, 2020) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 2
    Online Resource
    Online Resource
    Dark Data & AI Pipelines to Drive Ad Sales & Grow Audiences (2020)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 24 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Paul Barrett - Managing Director, Accenture Applied Intelligence Personalization drives more relevant conversations with advertisers and audiences. The key to personalization is data, algorithms and offers. Algorithms feed off data. The data environment is becoming more competitive and more regulated. AI at scale makes it possible to utilize internal and external data sources that were previously too complicated, too expensive or too big. The Dark Data sources can now be utilized to: • Enhance sales leads to drive better propensity scoring, better targeting and drive better sales interactions • Create a deeper understanding of audiences to create more relevant microsegments for better targeting, messaging and greater engagement. Companies that can master AI at scale can create Real-time Analytical Pipelines turning data science into Ai Enhanced customer interactions. Growing sales, Engagement and other key metrics. This talk will cover how companies are leveraging Dark Data and Ai pipelines to transform analytics into Ai enhanced interactions.
    Note: Online resource; Title from title screen (viewed March 24, 2020) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 3
    Online Resource
    Online Resource
    Process Automation using Machine Learning (2020)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 27 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Raktim Saha – Director, Digital Insights, CGI The focus of this talk is to showcase how Machine learning and AI is leveraged to radically outperform traditional loan-underwriting acceptance process for one of the largest lenders in US by utilizing a broader set of market, demographic, and various events data. Implementing an automated data-driven process in a large Enterprise and especially in a highly regulated industry has its own challenge spanning from data collection to accuracy of insights, and finally streamline the overall process. The speaker will cover the business, data, and technical aspects of this implementation.
    Note: Online resource; Title from title screen (viewed March 24, 2020) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    MPI Ethno. Forsch.
  • 4
    Online Resource
    Online Resource
    IoT and Analytics Condition Based Maintenance (2020)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 31 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Stanislaw Schmal Combining IoT and sensor analytics opens a new world of operations and maintenance efficiency. A real-world demonstrator of audio analytics and customized IoT device will be shown and its business application to condition based maintenance will be discussed in this session.
    Note: Online resource; Title from title screen (viewed March 24, 2020) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    MPI Ethno. Forsch.
  • 5
    Online Resource
    Online Resource
    All Models are Wrong, but Some are Useful. Especially with the Right Data (2020)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 18 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Alex Schwarm – VP/Head of Data Science at Dun & Bradstreet For many teams, the most challenging step in delivering useful results, is less about the modeling techniques and methods and more about having access to the right data with the appropriate data coverage of the domain of interest. In this talk, we will describe two specific use cases where data pays a crucial role: one around identifying supply chain risks and one related to prospect targeting. For the supply chain risk use case, we will describe how access to unique data assets reveals the impact of the Coronavirus on supply chains and how this impacts global businesses. We will also describe how some companies are offering data scientists the ability to access data to determine which data assets best solve their business analytics and modeling needs, with a particular focus on prospect targeting.
    Note: Online resource; Title from title screen (viewed March 24, 2020) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 6
    Online Resource
    Online Resource
    Model Monitoring Pipelines (2020)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 23 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Boryana Manz – Manager, Data Science at Capital One Model monitoring can make or break how models empower and deliver business value. This talk will highlight the key components for the proactive design of integrated and flexible model monitoring. It will include best practices for making the process seamless, flexible and actionable.
    Note: Online resource; Title from title screen (viewed March 24, 2020) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    MPI Ethno. Forsch.
  • 7
    Online Resource
    Online Resource
    Learning Node Embeddings in Transaction Networks (2020)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 21 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Jesse Barbour – Chief Data Scientist at Q2ebanking Due to the specialized and sophisticated nature of many commercially focused financial products offered by banks and fintechs, building recommender systems around those products is especially difficult. Taking inspiration from the field of neural language modeling, we will discuss an application of learning node embeddings on a large-scale financial transaction graph in order to solve this problem.
    Note: Online resource; Title from title screen (viewed March 24, 2020) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 8
    Online Resource
    Online Resource
    Minority Report : Can we predict emergencies (2020)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 24 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Michael Zelenetz – Analytics Project Leader at New York-Presbyterian Hospital Forecasting is widely used in a number of business, but can it be used to optimize operations in an emergency department? This talk will walk through the development of a forecasting model to predict future arrivals to the emergency department. We will review the fundamentals of forecasting, discuss feature engineering, and how to get your first forecast off the ground.
    Note: Online resource; Title from title screen (viewed March 24, 2020) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    MPI Ethno. Forsch.
  • 9
    Online Resource
    Online Resource
    New Frontiers in ML driven Customer Intelligence (2020)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 21 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Seemit Sheth – Head of Data Science at Capital One Micah Price – Principal Associate Data Scientist at Capital One Capital One is one of the pioneers of ‘Information based strategy’ which is essentially what we call today as data science. The world of data science in banking has evolved over time and now data science powers strategies in many diverse areas of a bank, aided by cutting-edge technologies. In this talk, we will go over a glimpse of its past, present and how it is changing banking for good as we move toward the future. In particular, we will also explore how cutting-edge algorithms and technologies are improving customer experiences.
    Note: Online resource; Title from title screen (viewed March 24, 2020) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    MPI Ethno. Forsch.
  • 10
    Online Resource
    Online Resource
    Leveraging Machine Learning and Open Data for Smart Cities (2020)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 31 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Priscilla Boyd – Senior Manager, Data Analytics at Siemens Mobility This presentation discusses how AI, machine learning and data publicly available is playing a role in smart cities, walking through applications developed using ML to solve practical transportation for smart cities globally.
    Note: Online resource; Title from title screen (viewed March 24, 2020) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    MPI Ethno. Forsch.
  • 11
    Online Resource
    Online Resource
    Leveraging Entity Resolution to Identify Customers in 3rd Party Data (2020)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 31 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Kelsey Redman – AVP, Data Science at Comerica Bank Purchasing 3rd party data on individuals can give great insights on customers, but first we have to know which individuals from that outside data source are actually customers and which are just prospects. Without a unique identifier like SSN or Driver’s License number from the 3rd party data, we have to use a combination of name, address, and demographic information to identify the matching customer. Between nicknames, misspelled names and addresses, and family members with similar names all at one address, this quickly becomes a difficult task involving heavy data cleanup and an increasingly complicated series of rules. In this presentation, we demonstrate some techniques to help resolve these entities across data sources by employing the use of supervised classification machine learning techniques to quantify and predict entity “likeness.” We showcase some of the challenges we faced with exploring other entity resolution methods, with manually labeling a comprehensive training set, and how this approach might extend to solve other data issues.
    Note: Online resource; Title from title screen (viewed March 24, 2020) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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    MPI Ethno. Forsch.
  • 12
    Online Resource
    Online Resource
    Applied Machine Learning for Spreading Financial Statements (2020)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 22 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Moody Hadi – Group Manager – Financial Engineering at S&P Global Market Intelligence Counterparty financial statements, particularly for small and medium enterprises can be difficult to handle. Financial analysts need to be able to distill out relevant line items in order to calculate their credit exposure to a counterparty for lending purposes. The solution solves a labor intensive, expert driven inefficient process and frees up the analysts to focus on their high value add operations. This involves combining Optical Character Recognition using pre-trained language neural networks, with context sensitive semantic matching. We will go over the developed ML pipleline and architecture.
    Note: Online resource; Title from title screen (viewed March 24, 2020) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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    Online Resource
    MPI Ethno. Forsch.
  • 13
    Online Resource
    Online Resource
    Who will fight for AI in Healthcare (2020)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 36 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Amy Daali - Chair at IEEE Engineering in Medicine & Biology Society With recent advancements in artificial intelligence, the healthcare industry is primed to benefit significantly from Machine Learning and Deep Learning technologies. This talk will answer the burning question on who is going to fight for AI in healthcare? New concepts such as “DIY healthcare” will be explored. We will discuss key important players who are going to lead the battle and drive AI adoption in 2020. Together, we will navigate the current Health Technology Landscape and uncover the different challenges that are preventing the implementation of AI. We will conclude the talk by exploring how we can improve collaboration between the Data Science and Medical community to speed up AI adoption in healthcare.
    Note: Online resource; Title from title screen (viewed March 24, 2020) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    MPI Ethno. Forsch.
  • 14
    Online Resource
    Online Resource
    Hands on Inquiry into Algorithmic Bias and Machine Learning Interpretability (2020)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 35 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Fatih Akici - Manager, Risk Analytics and Data Science at Populus Financial Group As intelligent systems deepen their footprints in our daily lives, algorithmic bias becomes a more prominent problem in today's world. The position of executives and data science leaders to this issue is generally reactive, in that, companies solely respond to the requirements coming from regulatory agencies. In this presentation, I am going to argue why the leaders should be proactive in identifying biases and how they will benefit from fixing them. I will demonstrate my point on an applied example.
    Note: Online resource; Title from title screen (viewed March 24, 2020) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
    Library Location Call Number Volume/Issue/Year Availability
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  • 15
    Online Resource
    Online Resource
    Testing in Xcode : Unit Testing, UI Testing, and Code Coverage (2019)
    [Erscheinungsort nicht ermittelbar] : Apress | Boston, MA : Safari
    Details
    ISBN: 9781484251928
    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 23 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn automatic testing in Xcode. Start by creating a simple test app that intentionally crashes in given scenarios. Then review the code to find obvious bad practices and issues. Discover why unit testing is important and perform a simple unit test. Work with test cases before adding functionality. Then increase code coverage and learn why it's important. Finally work with different parts of the app to test specific functionality. What You'll Learn Set up different UI tests for testing different parts of an app Perform simple unit test cases in a project Use test cases before adding functionality to ensure quality apps Who This Video Is For Professional developers or experienced programmers who want to incorporate best practices for testing their apps before publishing them.
    Note: Online resource; Title from title screen (viewed July 8, 2019)
    URL: lizenzpflichtig
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  • 16
    Online Resource
    Online Resource
    Spotlight on Cloud : The Future of Internet Security with Bruce Schneier (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: Long gone are the days when computer security was about data. Now, it’s about the much more critical and personal issues of life and property. The impact of this change means two things: Data authentication and integrity concerns will trump those of confidentiality The idea of an internet without regulations will be a thing of the past While these consequences are inevitable, we can prepare for them. First, by looking at previous attempts to secure these systems. Then, by considering the appropriate technologies, laws, regulations, economic incentives, and social norms we should focus on going forward. Recorded on April 4, 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 September 17, 2019)
    URL: lizenzpflichtig
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  • 17
    Online Resource
    Online Resource
    Red Hat Certified Engineer (RHCE) EX294 : Red Hat Ansible Automation (2019)
    [Erscheinungsort nicht ermittelbar] : Pearson IT Certification | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 7 hr., 45 min.)
    Edition: 3rd edition
    Keywords: Electronic videos ; local
    Abstract: The Sneak Peek program provides early access to Pearson video products and is exclusively available to Safari subscribers. Content for titles in this program is made available throughout the development cycle, so products may not be complete, edited, or finalized, including video post-production editing. 10+ Hours of Video Instruction Description Red Hat Certified Engineer (RHCE) EX294 Complete Video Course, 3/e: Red Hat Ansible Automation provides a solid understanding of all the topics required to pass the RHCE exam, including how to perform common automation tasks using Ansible and management of a Linux environment Overview Red Hat Certified Engineer (RHCE) EX294 Complete Video Course, 3/e: Red Hat Ansible Automation is all new and fully updated. This 10-hour video course provides a solid understanding of all the topics required to pass the RHCE exam and includes live demos, exam question walk-throughs and dynamic lightboard teaching. The student learns how to perform common automation tasks using Ansible as well as how to use common Ansible components to automate the management of a Linux environment. RHCE EX294 Complete Video Course covers all facets of the newly-updated RHCE exam. Instructor Sander van Vugt walks you through the topics using demos and labs to test the student's knowledge with real world scenarios. Each video lesson ends with a lab that provides an exercise so you can test your skills. Sander then provides a detailed solution to each lab, explaining how to solve for the exam objectives so you can get the experience you need to pass the test. Audio instruction throughout offers detailed explanations, tips, and configuration verifications. This engaging self-paced video training solution provides learners with more than 10 hours of video instruction from an expert trainer with more than 20 years of practical Linux teaching experience. Through the use of topic-focused instructional videos, you will gain an in-depth understanding of all topics on the Red Hat Certified Engineer (RHCE) exam, as well as a deeper understanding of Red Hat Enterprise Linux and Ansible. The combination of video, labs, and practice exams provides a unique offering that gives you a full toolkit to learn and excel on your exam. Topics include: Module 1: Introduction to Ansible Module 2: Using Advanced Ansible Solutions Module 3: Managing Systems with Ansible Module 4: Sample Exam About the Instructor Sander van Vugt has been teaching Linux classes sinc...
    Note: Online resource; Title from title screen (viewed September 27, 2019)
    URL: lizenzpflichtig
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  • 18
    Online Resource
    Online Resource
    Pragmatic AI and Machine Learning Core Principles (2019)
    [Erscheinungsort nicht ermittelbar] : Addison-Wesley Professional | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 4 hr., 1 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: 4+ Hours of Video Instruction Machine Learning is the scientific study of models and algorithms that train a computer to make predictions without explicit instruction. Machine Learning is a subset of Artificial Intelligence, which can be defined as computers that mimic human problem-solving. This video demonstrates the core principles of Machine Learning and AI, including supervised Machine Learning, unsupervised Machine Learning, neural networks, and social network theory. Learn to master the foundational concepts of AI and Machine Learning. The LiveLessons video starts with an overview of Artificial Intelligence and covers applications of AI across industries and opportunities in AI for individuals, organizations, and ecosystems. It also covers the difference between narrow, general, and super AI. Description Shore up the foundational knowledge necessary to work with Artificial Intelligence and Machine Learning! This LiveLesson video covers the core principles of Artificial Intelligence and Machine Learning, including how to frame a problem in terms of Machine Learning and how Machine Learning is different than statistics. Learn about fundamental concepts including nearest neighbors, decision trees, and neural networks. The video wraps up covering timely machine learning topics such as cluster analysis, dimensionality reduction, and social networks. Access the code repository for this LiveLesson at https://github.com/noahgift/fundamentals_ai_ml . About the Instructor Noah Gift is lecturer and consultant at UC Davis Graduate School of Management MSBA program the Graduate Data Science program, MSDS, at Northwestern, the Graduate Data Science program at UC Berkeley. He is teaching and designing graduate Machine Learning, AI, Data Science courses and consulting on Machine Learning and Cloud Architecture for students and faculty. These responsibilities include leading a multi-cloud certification initiative for students. Noah is a Python Software Foundation Fellow, AWS Subject Matter Expert (SME) on Machine Learning, AWS Certified Solutions Architect and AWS Academy Accredited Instructor, Google Certified Professional Cloud Architect, and Microsoft MTA on Python. Noah was selected to the SME Machine Learning team due to accomplishments in the area of Machine Learning on the AWS platform. He has published more than 100 technical publications, including several books on subjects ranging from Cloud Machine Learning to DevOps. Gift received an MBA fro...
    Note: Online resource; Title from title screen (viewed September 5, 2019)
    URL: lizenzpflichtig
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  • 19
    Online Resource
    Online Resource
    Content Marketing on The Web : Web Writing for Blogs, Business Sites, Sales Letters, and More (2019)
    [Erscheinungsort nicht ermittelbar] : Apress | Boston, MA : Safari
    Details
    ISBN: 9781484249598
    Language: English
    Pages: 1 online resource (1 video file, approximately 35 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Discover how to write for the web: either for your own brand or as a service that you provide to others. This video will include how to write a blog post, how to write website copy, how to write a persuasive sales script, and how to write SEO articles. The focus will always be on providing value and on understanding the value proposition of the brand that you are writing for. From there, you will look at methods you can use to grab attention, communicate clearly, keep the reader engaged and to encourage an emotional response. You'll cover the importance of content marketing for exposure as well as building trust, and just why writing is in many ways the currency of the web. Content is what brings the vast majority of people to a website. They search Google for content, they return to a website because they enjoyed the content. It is also what sells a product – and simply by improving a sales script, a company can massively increase conversions. Companies that don’t understand how to write for the web will therefore be at a massive disadvantage. This is common to see: we all have encountered countless business sites with muddled messages that fail to explain what the company actually does and why the reader should care. What You Will Learn Study methods you can use to increase engagement and grab attention Understand the role of content and content marketing Write content for email, white papers, press releases, and more Who This Video is For Businesses that are currently failing to make a splash with their websites and social media, or that could be doing better. Anyone looking to increase sales of a product, to increase regular visitors to a blog, or to learn a valuable skill they can sell/use to augment a web development business.
    Note: Online resource; Title from title screen (viewed May 4, 2019)
    URL: lizenzpflichtig
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  • 20
    Online Resource
    Online Resource
    Branding and Design : Creating a Highly Memorable Brand for the Web (2019)
    [Erscheinungsort nicht ermittelbar] : Apress | Boston, MA : Safari
    Details
    ISBN: 9781484249581
    Language: English
    Pages: 1 online resource (1 video file, approximately 28 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Create a brand online through the use of web design, graphic design (Illustrator and Photoshop), outsourcing, social media, and various other strategies. The objective of this video is to help you create a coherent design that speaks to the mission statement of the brand, and that will increase audience engagement and loyalty. The main strategy is to create a brand design that is unique to the business and that has a specific buyer persona in mind (not to try and ‘appeal to everyone’). This will reference Simon Sinek’s ‘Golden Circle’. From there, a logo can be designed or outsourced to reflect that mission statement. This should be simple, re-useable, scalable, and non-cliched, and the design process may involve a mood board. The design should be a vector file and we will look at the technical skills necessary to create such a design. The same branding should then be used through a website, and will help to inform design decisions, as well as across social media. The aim here is 'be everywhere' and 'be consistent'. We will discuss how brand strategy can even influence product design, using Apple as the perfect example. We will also discuss branding in the context of content marketing. What You Will Learn Create a design aesthetic that expresses your company's valuers and ethos Choose a mission statement and find a buyer persona to help you meet your goals Study how you can create and maintain a brand Who This Video is For New startups, entrepreneurs, bloggers, and sole traders looking to create a strong platform online. Businesses currently operating with drab and uninspired branding that are losing potential leads as a result.
    Note: Online resource; Title from title screen (viewed May 9, 2019)
    URL: lizenzpflichtig
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  • 21
    Online Resource
    Online Resource
    Blockchain in Swift : Decentralized iOS Programming (2019)
    [Erscheinungsort nicht ermittelbar] : Apress | Boston, MA : Safari
    Details
    ISBN: 9781484253823
    Language: English
    Pages: 1 online resource (1 video file, approximately 48 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Implement Blockchains in iOS applications using the Swift programming language while working with the basics of blockchain development. In the first part of this video, the logic behind blockchains will be explained and then the same logic will be implemented in iOS application development. You’ll work to develop a sample application where you'll allocate two accounts which will have a certain amount of bitcoins in them. Then you'll transfer those bitcoins between those accounts using blockchain technology by clicking transfer buttons in the application. What You Will Learn Implement blockchains in iOS applications Define blockchains in Swift Develop a sample blockchain application Who This Video Is For Experienced Swift developers who want to work with blockchains and decentralized programming.
    Note: Online resource; Title from title screen (viewed September 27, 2019)
    URL: lizenzpflichtig
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  • 22
    Online Resource
    Online Resource
    Artificial Intelligence Conference 2019 - Beijing, China (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 3 hr., 26 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: A unique keynote speech by Yangqing Jia, the leader of Alibaba’s AI and Big Data organization. A revealing talk by Ion Stoica (UC Berkeley) describing some the AI projects underway at UC Berekely's renowned RISELab. A thoughtful presentation by Long Wang, VP of TenCent Cloud, illustrating what TenCent believes AI will do for the cloud. These are just three of the illuminating talks given by the many AI experts from China, the U.S., and elsewhere who gathered to speak at O'Reilly Media's Artificial Intelligence Conference Beijing June 2019. This video compilation gives you the opportunity to see all of the best presentations from AI Beijing—it contains more than 60 hours of material to review on your schedule. AI Beijing's unique focus is applied AI—bridging the gap between AI developments in research and their commercial applications in business and industry. If you want to understand how AI will change the business landscape, or are working with deep learning or AI (or plan to be)— this video compilation is for you. Highlights include: Complete video recordings from the best of AI Beijing June 2019—this video compilation contains hours of material to review at your own schedule. 55% of the presentations are in English, 42% are in Chinese, and 3% are in English and Chinese. Keynote speeches by AI thought leaders such as Maria Zhang (LinkedIn), Pete Warden (Google Brain Team), Michael James (Cerebras), Hao Zheng (PlusAI), and Tim Kraska (MIT). Tutorials in Chinese, including Intels' Zhen Zhao's exploration into the OpenVINO toolkit and Microsoft's Henry Zeng, Lu Zhang, and Xiao Zhang's introduction to automated machine learning using Python and AutoML. Tutorials in English, such as Alejandro Saucedo's (The Institute for Ethical AI & Machine Learning) practical guide to de-mystifying machine learning bias and Richard Liaw (UC Berkeley RISELab) on how to build reinforcement learning models and AI applications with Ray. "Implementing AI" sessions presented in Chinese, such as Zhenxiao Luo (Uber) on how to run big data and machine learning systems at scale; Hui Xue (Microsoft) on the latest automated machine learning advances at Microsoft Research Asia; and Guoqiong Song (Intel) and Luyang Wang (Office Depot) on how Home Depot's real-time recommendation system was built using Analytics Zoo on BigDL and Apache Spark "Implementing AI sessions" delivered in English, including Google's Kaz Sato's examination of ML operations and Kubeflow pipelines; Rak...
    Note: Online resource; Title from title screen (viewed June 28, 2019)
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    Using AutoML to automate selection of machine learning models and hyperparameters (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 43 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Automated machine learning (AutoML) enables both data scientists and domain experts (with limited machine learning training) to be productive and efficient. In recent years, AutoML has fostered a fundamental shift in how organizations approach machine learning, making it more accessible to both experts and nonexperts. Most real-world data science projects are time-consuming, resource intensive, and challenging. Besides data preparation, data cleaning, and feature engineering, data scientists often spend a significant amount of time on model selection and tuning of hyperparameters. Automated machine learning changes that, making it easier to build and use machine learning models in the real world. Francesca Lazzeri and Wee Hyong Tok (Microsoft) lead a gentle introduction to how AutoML works and the state-of-art AutoML capabilities that are available. You’ll learn how to use AutoML to automate selection of machine learning models and automate tuning of hyperparameters. Topics include: An introduction to AutoML How AutoML works The libraries and cloud services that support AutoML An energy demand forecasting use case How to get started with automated machine learning 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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    Test in production : Yes, you can (and you should) (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 32 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Testing in production has gotten a bad rap. People act like testing in production implies you aren’t doing due diligence with your tests before production. But it’s more like a fact of life: you can only catch the easy bugs in staging—the known-unknowns, the things you predicted would fail, and the things that have failed before. Which isn’t nothing, but it’s no better than running tests on your laptop. Most interesting problems are only going to manifest under real workloads, on real data, with real users doing unpredictable things under real concurrency and resource pressure. So you should use much fewer of your scarce engineering cycles poring over staging and much more of them building guard rails for prod. Production—where your customers live—is the only environment that matters. Time spent interacting with nonprod systems is wasted time. Replicas are not valuable for helping build your instincts, your skill set, your intuition. Secondary environments actually train you to expect faulty assumptions and to take dangerous shortcuts and run terrifying commands. You should force people to develop and test on production as much as possible and interact with production every day. Charity Majors (Honeycomb) dives into tooling and shares ways to harden production and make it safe for engineers to do their work directly on it—from deploys and canarying to feature flags, instrumentation and observability, human practices and workflows, and much more. 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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    Tableau LiveLessons (2019)
    [Erscheinungsort nicht ermittelbar] : Addison-Wesley Professional | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 2 hr., 50 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: 4+ Hours of Video Instruction Put learning into practice with Tableau LiveLessons for the aspiring visual data storyteller. There is a data revolution happening across the globe. From academics to politics and everywhere in between, the world’s stories are being told through their data points. Although telling stories about data isn’t new, we are now telling them in ways that are more meaningful and impactful than ever before as an emerging new class of visualizations attempts to tell the world’s stories through the power of data visualization. However, visual data storytelling is not an inherent skill, and data stories differ from traditional storytelling in many ways. Further, while robust visualization tools support rich and diverse forms of visual data storytelling capabilities, crafting a compelling data narrative is not a process that we can rely on a tool to do for us. These lessons provide a hands-on foundation for users to learn how to craft visual data narratives using the most appropriate visualizations, apply visual design to engage their audience, and purposefully structure a narrative framework to deliver a compelling, actionable data story that invites discovery, solicits new questions, or offers alternative explanations–all using one of the most powerful and ubiquitous visualization tools on the market today, Tableau. Skill Level Beginner Learn How To- Tell visual stories that communicate insights and make an impact Leverage questions to design logical and fruitful data collection and analysis Create important graphs in Tableau and know which chart to use Utilize concepts of design in data visualization and storytelling Storyboard your story for your message based on your audience Direct your audience's attention to the most important parts of your data story Design effective business presentations to showcase your data story with Tableau Who Should Take This Course Analysts sharing the results of their data discovery or analysis Students communicating data for reports or presentations Teachers helping learners (of any age) to cultivate visual data literacy Executives and business managers reporting data-driven results or metrics Journalists giving data the starring role in their editorials Course Requirements A willingness to learn how to tell stories through data Access to Tableau Desktop (Windows or Mac), version 10 or higher Related Files The supplemental content for this LiveLesson can be downloaded from Githuub at: https:...
    Note: Online resource; Title from title screen (viewed February 12, 2019)
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    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)
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    Spotlight on Data : Data Storytelling with Mico Yuk (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 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)
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    Spotlight on Cloud : The Hidden Costs of Kubernetes with Bridget Lane (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 0 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: If you’re considering Kubernetes, you’ve probably thought about the potential time and cost savings you could stand to gain. At Gannett and USA TODAY, migrating to Kubernetes cut their daily infrastructure spend in half and reduced their network failover time from almost four hours to about 10 minutes. These are huge savings for any company. That said, there were a number of costs to migrating that they didn't anticipate. Gannett’s migration to Kubernetes had a ripple effect through its entire stack—from its CI pipelines to its approach to monitoring and even employee happiness. In this case study, Bridget Lane, Gannett’s manager of developer solutions, details the problems her team faced while migrating and explain how they dealt with them. Recorded on September 19, 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 4, 2019)
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    Redux Recipes (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781787282766
    Language: English
    Pages: 1 online resource (1 video file, approximately 3 hr., 0 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Develop complex and maintainable web applications using Redux About This Video Combine the power of Redux with popular JavaScript libraries to make consistent web applications Explore various advanced techniques with this recipe-based guide to find a solution to numerous common problems you might come across while using Redux Learn to structure and maintain your web application with predictable state containers In Detail State management is absolutely critical in providing users with a well-crafted experience with minimal bugs. Redux provides a solid, stable, and mature solution to managing state in your React application. In this course, you’ll explore advanced state management techniques, router integration, and other common problems that you might encounter while developing your applications. The recipe-based approach allows you to quickly identify your problem and find a solution to it. This course also consists of various recipes that will help you to understand different test-case scenarios created in Redux. Once you are well-acquainted with Redux, the course will explicitly show you how they work in developing a consistent application with React and Angular. The code bundle for this video course is available at https://github.com/PacktPublishing/-Redux-Recipes Downloading the example code for this course: You can download the example code files for all Packt video courses you have purchased from your account at http://www.PacktPub.com . If you purchased this course elsewhere, you can visit http://www.PacktPub.com/support and register to have the files e-mailed directly to you.
    Note: Online resource; Title from title screen (viewed February 28, 2019)
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    OSCON 2019 - Portland, Oregon (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 160 hr., 43 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local ; Electronic videos
    Abstract: OSCON Portland 2019 brought together a vibrant and diverse collection of talented speakers (open source leaders from around the globe) who do amazing things with open source technologies. This outstanding group provided the conference attendees (thousands of software developers, programmers, architects, engineers, CxOs, hackers, geeks, and analysts) with the opportunity to explore the latest open source tools and technologies; get expert in-depth training in crucial languages, frameworks, and best practices; and gain exposure to the open source stack in all its possible configurations. This video compilation offers you the chance to see and hear the best of OSCON Portland 2019. If you want to know how to build an open source culture at your company, work in a cloud environment that isn't always open source-friendly, understand how machine learning can make or break your code, or implement new technologies like Kubernetes and TensorFlow, then getting the OSCON Portland 2019 video compilation is for you. Highlights include: Complete video recordings of OSCON Portland 2019’s best keynotes, tutorials, and tech sessions offering hours of material to study and absorb at your own pace and schedule Keynotes, including Adam Jacob (Chef) on the war for the soul of open source; Kay Williams (Microsoft Azure) on lessons learned building a strong Kubernetes/VSCode open source community; Adrian Cockcroft (AWS) on leveraging cloud vendors to boost open source business success; and Pete Skomoroch (Workday) on the urgent need for a new open source ML development stack Tutorials offering deep dives into open source tech like Apache Kafka, Rust, extended Berkeley Packet Filters, Spring/Spring Boot, Ethereum DApps, Jenkins 2, Vault/Kubernetes, and Kubeflow The OSCON Business Summit: sessions offering an insider’s look at the open source implementations that have the most profound impact on business with talks by open source specialists at Uber, Pacific Life, Verizon Media, The Home Depot, Baidu, the BBC, and more Open Source do-it-now sessions, including Deb Nicholson’s (Software Freedom Conservancy) whirlwind tour of what not to do when running an open source project; Russell Rutledge’s (Nike) take on how to build an open source culture at your company; and Angie Jones (Applitools) and a panel of experts from Persea Consulting, Red Hat, Magento, and ForgeRock on the best ways to build and maintain open source communities Emerging Languages and Frameworks session...
    Note: Online resource; Title from title screen (viewed July 17, 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 Software Architecture 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 1 hr., 49 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. Thousands of software architects, aspiring software architects, senior developers, system leads, tech leads, software engineers, data architects, and tech team managers came together at O’Reilly Media’s Software Architecture Conference Berlin 2019 to learn how to design, build, and improve the architectures that are the foundation of all modern software systems. Who did the attendees learn from? They learned from experts like senior software architect Carola Lilienthal (Workplace Solutions), a 30-year software engineering vet, who broke down the causes and costs of technical debt and then outlined the ways to eliminate it. And they learned from site reliability expert Jibby Ayo-Ani (Welkin) as she described Google’s BeyondCorp, a new enterprise security model in cloud computing that every software architect needs to understand. These speakers and gave SACON Berlin 2019’s attendees what they hoped to receive: The knowledge and insights required to become the best software architects they could be. Get this video compilation of SACON Berlin 2019 and you’ll gain the opportunity to increase your skill set and move forward in your software architecture career. Highlights include: Complete video coverage of SACON Berlin 2019’s best keynotes, tutorials, and technical sessions—this compilation contains hours of SACON talks to study and absorb at your own pace and schedule. Keynote addresses from software architecture’s most incisive thinkers, including Bosatsu Consulting President Brian Sletten, ThoughtWorks principal technology consultant Zhamak Dehghani, and the Cloud Native Computing Foundation’s Director of Ecosystem, Cheryl Hung. Hands-on tutorials covering subjects like reusable information architecture; event storming for domain-driven design modeling; and building, specifying, and testing APIs with microservices. Application Architecture sessions, including Patrick Kua (Chief Scientist, N26) on scaling out architectural decision-making during rapid growth; Vladik Khononov (Chief Architect, Naxex) on DDD’s most common mistakes; and Paddy Fagan (Chief Architect, IBM Watson Care Manager) on implementing continuous architectural refactoring in a SaaS offering. Distributed Systems sessions, such as on the need for autonomous APIs in a landscape of impossibly complex distribu...
    Note: Online resource; Title from title screen (viewed November 6, 2019)
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    Oracle Cloud User Security : Providing for Separation of Duties and Appropriate Access by Job Function (2019)
    [Erscheinungsort nicht ermittelbar] : Apress | Boston, MA : Safari
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    ISBN: 9781484255643
    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 3 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Enhance the security of your Oracle cloud environment by providing users appropriate access for their respective job functions, and by providing for separation of duties such that no single user has enough access by which to exceed their level of authority. See how to think through and plan for the access requirements of technical experts such as cloud administrators and database administrators through to business-level users such as those accessing cloud applications and databases. Make use of your own enterprise identity management system, or use Oracle Identity Cloud Service. The video begins by showing how to create a plan based on enterprise roles for managing the database environment in the cloud. This plan includes a component on separation of duties. The video goes on to show how to create groups from the plan, and how to create users and assign users to groups. There are default groups and custom groups, so the video will cover creating and managing custom groups as well as the default ones. Connections to cloud services and databases are tested as a final step to verify the users and groups that have been created. What You Will Learn Design a role-based plan for managing users in the Oracle Cloud Create users in the Oracle Cloud for services and databases Manage roles and groups Manage single-sign-on in Oracle Identity Cloud Service Create customized groups through Oracle Identity Cloud Service Test to ensure users can connect to the cloud service and database server Verify user groups by showing that the right roles have been assigned Who This Video Is For Database administrators who are just starting to use Oracle’s cloud services, or who are getting ready to migrate to the Oracle cloud. For security administrators who want to learn best practices related to separation of duties and for centrally managing cloud users.
    Note: Online resource; Title from title screen (viewed October 25, 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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    Expert Playlist Intro : Learn How To Write A Great Technical Book, By Example (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 3 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 books as great examples of how to write a technical book.
    Note: Online resource; Title from title screen (viewed August 25, 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
    Details
    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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    Enabling insights and analytics with data streaming architectures and pipelines using Kafka and Hadoop (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 40 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: In a large global health services company, streaming data for processing and sharing comes with its own challenges. Data science and analytics platforms need data fast, from relevant sources, to act on this data quickly and share the insights with consumers with the same speed and urgency. Join Mohammad Quraishi (Cigna) to learn why streaming data architectures are a necessity—Kafka and Hadoop are key. Mohammad outlines architectures centered around the Hadoop Platform and Kafka that were implemented to support a variety of integration and analytics requirements. Topics include: Enabling streaming to and from relational sources and files using custom frameworks that automate and speed up workflows Combining the polyglot techniques with Kafka API to support various streaming solutions Combining data driven techniques to support consumers through a simple streaming architecture and microservices How HBase, Kudu, and Kafka Streams are used to reduce latency between these microservices and frontend application APIs Enabling the consumption and sharing of data sources and results using streams Enabling Spark Structured Streaming, Flink, and Spark ML on these streams Enabling data sync between on-premises data lakes and the cloud Supporting cloud native architectures that enable machine learning in the cloud 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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    Data Analytics and Machine Learning Fundamentals LiveLessons Video Training (2019)
    [Erscheinungsort nicht ermittelbar] : Addison-Wesley Professional | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 7 hr., 40 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: More than 7.5 Hours of Video Instruction Overview Nearly every company in the world is evaluating its digital strategy and looking for ways to capitalize on the promise of digitization. Big data analytics and machine learning are central to this strategy. Understanding the fundamentals of data processing and artificial intelligence is becoming required knowledge for executives, digital architects, IT administrators, and operational telecom (OT) professionals in nearly every industry. In Data Analytics and Machine Learning Fundamentals LiveLessons , experienced CCIEs Robert Barton and Jerome Henry provide more than 7 1/2 hours of personal instruction exploring the principles of big data analytics, supervised learning, unsupervised learning, and neural networks. In addition to delving into the fundamental concepts, Barton and Henry address sample big data and machine learning use cases in different industries and present demos featuring the most common tools (such as Hadoop, TensorFlow, Matlab/Octave, R, and Python) in various fields used by data scientists and researchers. At the conclusion of this video course, you will be armed with knowledge and application skills required to become proficient in articulating big data analytics and machine learning principles and possibilities. Skill Level Beginner to intermediate data analytics/machine learning knowledge Learn How To * Understand how static and real-time streaming data is collected, analyzed, and used * Understand the key tools and methods that enable machines to learn and mimic human thinking * Bring together unstructured data in preparation for analysis and visualization * Compare and contrast the various big data architectures * Apply supervised learning/linear regression, data fitting, and reinforcement learning to machines to yield the information results you’re looking for * Apply classification techniques to machine learning to better analyze your data * Exploit the benefits of unsupervised learning to glean data you didn’t even know you were looking for * Understand how artificial neural networks (ANNs) perform deep learning with surprising (and useful) results * Apply principal components analysis (PCA) to improve the management of data analysis * Understand the key approaches to implementing machine learning on real systems and the considerations you must make when undertaking a machine learning project Who Should Take This Course * Anyone who wants to learn about machine learni...
    Note: Online resource; Title from title screen (viewed April 2, 2019)
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    Building Apps with SwiftUI : Custom Views and Common Use Cases (2019)
    [Erscheinungsort nicht ermittelbar] : Apress | Boston, MA : Safari
    Details
    ISBN: 9781484253106
    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 6 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Create a basic application flow with SwiftUI involving login and a user dashboard interface in this video. Discover the new file structure introduced by SwiftUI and how it uses structs instead of classes for Views. Then learn about common layout elements such as Text, Images, HStack, VStack, ZStack, and NavigationViews. After understanding the structure and elements, dive in to create a login layout and a user authentication backend. Then once you've got your user logged in, create a dashboard layout for your users with SwiftUI. Finally learn to troubleshoot and polish up your new interfaces. What You Will Learn Create login and dashboard interfaces Troubleshoot common SwiftUI interface issues Incorporate NodeJS for authentication and backend work Who This Video Is For iOS developers with a basic familiarity of the Swift language who would like to use SwiftUI to design easy, elegant, and powerful interfaces.
    Note: Online resource; Title from title screen (viewed August 19, 2019)
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    Brains considered harmful : How cognitive biases undermine your software architecture (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 45 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Most software engineers come up through the ranks as coders and believe that the valuable lessons they’ve learned from their years in the trenches are an infallible guide to the future. While experience is certainly useful, the emerging field of cognitive psychology has another story to tell: the real reasons for our decisions aren’t entirely the subject of our conscious choice—or even awareness. Ian Varley (Salesforce) covers the emerging field of cognitive biases—bugs in our mental operating system—and takes a cold, hard look at how these mental blind spots defeat our attempts to build quality software in every domain. (If you’ve read books like Thinking Fast and Slow and You Are Not So Smart , you’ll be familiar with the basic idea.) While awareness of cognitive biases is a good life skill in general, it’s particularly critical if you’re in a software architect role, because your opinions set the conditions for massive amounts of work by other engineers. As such, it’s worth the time to thoroughly debug your own process for learning and making important decisions. Ian explains why the sunk cost fallacy means you’re not throwing things out fast enough; how confirmation bias can sneak into even the most data-driven decisions; how hindsight bias is obscuring the real lessons you might have learned from that failed project; how priming and fixation is shooting down your most promising inputs; and how arguing over architectural decisions is unlikely to help anybody. (See also: “Nobody ever changed their mind between Vim and Emacs.”) Most importantly, Ian shares concrete techniques you can use to check your own decision making for these unwelcome guests. We might not be capable of being perfectly rational beings, but we can be a lot less dumb. 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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    Autodesk Revit in 4 Hours (2019)
    [Erscheinungsort nicht ermittelbar] : Packt Publishing | Boston, MA : Safari
    Details
    ISBN: 9781838551728
    Language: English
    Pages: 1 online resource (1 video file, approximately 4 hr., 19 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Efficiently create models that capture design intent with Autodesk Revit About This Video An overview of the major tools needed to build a successful model. A brief discussion of advanced methods used for many of the tools covered. An introduction to creating custom elements to make your design and model unique. In Detail Autodesk Revit boasts powerful tools that allow you to efficiently plan and manage your projects and visualize your designs. You will begin by moving around in Revit before discussing the tools you'll need to begin setting up a project. Then you'll cover the basic tools and methods for building a 3D model using all of the most common tools. Then you will create custom elements that allow you to add a level of detail and design to make your projects unique. You will then learn 2D modeling; we will be looking at many of the tools that help round-out a good drawing set; from dimensions, to two-dimensional linework and fill regions - everything from the stock materials built into Revit, to creating custom textures to get the look you're after. After learning 2D models you will create 3D views, all of the settings that are associated with the internal rendering engine Finally, we will discuss tools and processes by which you can produce a full construction document or presentation drawing set; this will include title blocks, sheets, and custom schedules, as well as how to save a set of drawings as a PDF or print them as hard copies.
    Note: Online resource; Title from title screen (viewed April 23, 2019)
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  • 42
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    AWS Account Setup Best Practices (2019)
    [Erscheinungsort nicht ermittelbar] : Addison-Wesley Professional | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 2 hr., 18 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: AWS Account Setup Best Practices Sneak Peek The Sneak Peek program provides early access to Pearson video products and is exclusively available to Safari subscribers. Content for titles in this program is made available throughout the development cycle, so products may not be complete, edited, or finalized, including video post-production editing.
    Note: Online resource; Title from title screen (viewed November 7, 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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    Advanced Scenarios in Azure Functions (2019)
    [Erscheinungsort nicht ermittelbar] : Apress | Boston, MA : Safari
    Details
    ISBN: 9781484244081
    Language: English
    Pages: 1 online resource (1 video file, approximately 45 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: In this video on Azure Functions, you will learn about the most relevant advanced features of Azure Functions. The video is broken down into concise yet complete segments so that you can discover how to write, debug, and diagnose Azure Functions on a need-to-know basis. As various cloud offerings move towards serverless computing, Azure Functions has emerged as Microsoft Azure’s serverless computing platform. This video goes a step beyond coding in the browser and introduces you to a typical view of Azure Functions, including writing in VS Code, debugging, and diagnosing issues. What You Will Learn Orchestrate Azure Functions Diagnose using Kudu Debug Azure Functions Write Azure Functions in VS Code Who This Video Is For NodeJS or C# developers who are interested in learning about Azure Functions. It is a 200 level video; Viewers should have a basic level of familiarity with Azure Functions.
    Note: Online resource; Title from title screen (viewed January 7, 2019)
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    Turn devices into data scientists—at the edge (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 36 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Today’s approach to processing streaming data is based on legacy big-data centric architectures, the cloud, and the assumption that organizations have access to data scientists to make sense of it all—leaving organizations increasingly overwhelmed. Simon Crosby (SWIM.AI) shares a new architecture for edge intelligence that turns this thinking on its head. Edge intelligence (encompassing analytics, learning and prediction, and edge computing) can frequently be accomplished on the fly on streaming data, cheaply, at the edge, without data scientists. Simon demonstrates how you can save up to $5,000 a month in cloud processing and storage costs while delivering accurate predictions that can transform outcomes, using well-established architectural pillars, such as the distributed actor model, to process voluminous real-time data at the edge, along with the rich commons of open source analytics and learning tools like Flink and Spark, on nothing more than a $200 device such as an NVIDIA Jetson. The key insight is to use streaming data to build a digital twin model on the fly at the edge, avoiding a ton of complexity and infrastructure costs. Instead, a user defines the entities in their environment (e.g., traffic intersections, compressors, or assembly robots) that deliver data. Using the stateful distributed actor model, you can dynamically build a digital twin (actor) model of the real-world from the data, linking twins based on their relationships. Each digital twin reduces, labels, and analyzes its data and self-trains a machine learning model to predict future performance, at the edge, discarding the original data. This method needs only a tiny fraction of the resources of a big data solution and delivers results in real time. As a result, it bypasses the dev, ops, and data science challenges of edge intelligence, effectively turning devices into data scientists—or at least, building data science twins for entities in the real world. 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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    Recommendation engines and mobile gaming (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    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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    Deploying and Migrating to Azure Web Apps : Optimizing Web Server Workloads (2019)
    [Erscheinungsort nicht ermittelbar] : Apress | Boston, MA : Safari
    Details
    ISBN: 9781484255926
    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 10 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Learn everything you need to know to get started with Azure web apps, including deployment, key features, and benefits, to monitoring. This video introduces you to Azure App Service, and more specifically, Azure web apps. Starting from a base deployment of an Azure-running web site, you will learn about several cloud-native features of the service. These are key in allowing you to run highly available and production-ready web applications on Azure, without the underlying web server virtual machines. You will also learn about integration with Visual Studio and Visual Studio Code, to ease the overall deployment and management of such web apps from a development and sysadmin perspective. What You Will Learn Understand Azure web app core features and functionalities Deploy scalable and high-available web apps across regions Leverage Azure web app scaling features Publish web applications from Visual Studio and Visual Studio Code Run highly available web apps across multiple Azure regions Use Azure Monitor for monitoring and troubleshooting Azure web apps Who This Video Is For Developers who want a brief introduction to the value and uses of Azure web apps.
    Note: Online resource; Title from title screen (viewed November 4, 2019)
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    CCNA 200-301 (2019)
    [Erscheinungsort nicht ermittelbar] : Pearson IT Certification | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 14 hr., 44 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local ; Electronic videos
    Abstract: Sneak Peek The Sneak Peek program provides early access to Pearson video products and is exclusively available to Safari subscribers. Content for titles in this program is made available throughout the development cycle, so products may not be complete, edited, or finalized, including video post-production editing.
    Note: Online resource; Title from title screen (viewed October 15, 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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    Beyond accidental architecture (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 18 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Software systems always express some form of architecture. Many times those architectures reflect the mere circumstances and microtrends prevailing at various times. But long-term success doesn’t happen by accident. When approached deliberately, software architecture and design can produce benefits for teams in a variety of ways. James Thompson (Cingo Solutions) demonstrates how to assess approaches and make decisions based on what matters to your team and your projects by answering the following guiding questions: What is software architecture? What decisions are architectural? How do you discuss software architecture? How do you document architectural decisions? How do you encourage continued learning? These questions give you a framework for thinking about how to do software architecture in a collaborative way. Software development is a collaborative effort, and software architecture should be also. Software architecture is something that every developer should be equipped and empowered to engage with—leading to a more collaborative way of developing and maintaining your software systems. This session was recorded at the 2019 O'Reilly Software Architecture Conference in New York.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
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    AWS Certified Developer (Associate) (2019)
    [Erscheinungsort nicht ermittelbar] : Pearson IT Certification | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 14 hr., 46 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: 14+ Hours of Video One Line Sell More than 14 hours of video instruction preparing the viewer for the AWS Associate Level Certified Developer exam by discussing and demonstrating the services included in the published blueprint of the exam, including AWS CLI & SDK, IAM, VPC, EC2, Route53 DNS, S3, DynamoDB, etc. Overview This course, “AWS Certified Developer Complete Video Course” focuses on the role-based certification, AWS Developer Associate. According to Amazon, “this exam validates proficiency in developing, deploying, and debugging cloud-based applications using AWS.” Amazon Web Services currently has over 130 individual services available for use. Each service falls into an overarching category such as compute, storage, database, networking, etc. The AWS Developer Associate focuses on those services and concepts relevant to developers using, or intending to use, AWS services to create their applications. This course covers the published blueprint for the Associate level Certified Developer exam. It’s important to note that this course is not intended to teach you to how program or develop applications. The goal is to help you understand the services that are available to run the applications you develop through live demonstration. Each lesson begins with a walk-through to provide an overview of the topic and then goes into demonstration mode. The majority of the demonstrations in this course are accomplished with a free AWS Trial Account so you can follow along. This course takes a lab-based approach to teaching you, which means we will focus on how to develop throughout the training so you can get some hands-on experience working in AWS. You will also learn about the objectives in the exam, but the emphasis is on doing so you can gain the experience needed to actually develop in AWS as well as pass the test. Each lesson has a lab-based exercise that walks you through concepts and also allows you to dive into a project. Lab files are included as downloads with the course so you can work alongside the author and work on projects." Nick Garner has co-founded an IoT company that runs entirely on AWS infrastructure that he manages. He has certifications in AWS, CEH, CISSP and 2 CCIEs (routing/switching and security). He works with Amazon Web Services design on a daily basis, particularly with respect to extending enterprise services into cloud service providers such as Amazon AWS, Microsoft Azure, and Google Compute. Topics include: Module ...
    Note: Online resource; Title from title screen (viewed January 9, 2019)
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    Automating DevOps for machine learning (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 40 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: You’ve spent hundreds of hours cleaning your data, engineering features, and training and tuning your model to pinpoint accuracy. But now it’s time to deploy your model into production. Whether you lead a team of data scientists or are one yourself, you know how time-consuming and problematic deployment can be. Language and environment incompatibilities, manual and duplicative processes, out-of-control costs, and poor communication can destroy all the work you’ve put into building models and slow your machine learning efforts. Learning common deployment architectures for machine learning in the real world and understanding how to build your model for a production environment can help you avoid pitfalls when scaling up. Diego Oppenheimer (Algorithmia) discusses common problems and solutions and shares best practices from leading organizations that have solved the deployment headache. 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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    Artificial intelligence on human behavior : New insights into customer segmentation (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    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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    Amazon Web Services AWS LiveLessons 2nd Edition (2019)
    [Erscheinungsort nicht ermittelbar] : Addison-Wesley Professional | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 17 hr., 14 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: More Than 17 Hours of Video Instruction More than 17 hours of video instruction on Amazon Web Services with coverage on cloud computing and available AWS services, as well as a guided hands-on look at using services such as EC2 (Elastic Compute Cloud), S3 (Simple Storage Service), and more. Overview Amazon Web Services (AWS) LiveLessons is a unique video product designed to provide a solid foundational understanding of the Amazon Web Services (AWS) infrastructure-as-a-service (IaaS) products. The course covers concepts necessary to understand cloud computing platforms, distributed computing, multi-tier architectures, virtual machines, storage, databases, analytics, high availability, and much more. This course has been designed to show just how simple and cost-effective it is to achieve a superior level of high-availability, fault-tolerance, security, and reduced operational burden in your infrastructure and applications. Detailed throughout the course are a number of use cases designed to spark your imagination and exemplify well-architected solutions within the rich and varied ecosystem that is Amazon Web Services. You can also use this video as a secondary resource to help you study for the AWS Cloud Practitioner and Solutions Architect Exams. Since the first edition of this course, AWS has added many new services to their offerings, as well as many new features to existing services. The AWS web-based management console has also seen significant updates and improvements. In this second edition, many of those new services and features are covered, and all new diagrams have been provided to more accurately represent those you will see in a real-world scenario. The new edition also includes all new demos to account for changes in the AWS management console user interface. Amazon Web Services (AWS) LiveLessons contains 14 independent video lessons totaling almost 13 hours of instruction. The videos contain in-depth instruction using live demos, slide instruction, and video captures. Demonstrations of Amazon Web Services and third-party cloud solutions are included to provide necessary context and experience for further study and use of AWS. Skill Level Beginner/All levels Learn How To Get started with AWS, including networking, computing, storage, managing databases, and security Understand cloud-computing platforms, and how AWS fits into them Use EC2, CloudWatch, S3 Buckets, and more Use IAM, VPC, NACLs, AMI, ECS, EKS, EBS, and other various t...
    Note: Online resource; Title from title screen (viewed March 26, 2019)
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    Keys to Leading Highly Effective Data Science Teams (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 30 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Darby Laffoon – Sr Manager, Big Data Platform Engineering at Charles Schwab In this session, we will walk through the various aspects of how to build and manage effective data science teams, and how to navigate the many challenges that come with such an undertaking. While there is no right or wrong, experience tells us that there are a multitude of ways to approach any challenge therein, and that’s where we will focus much of our energy.
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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    The Open Data Science Platform (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 25 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Andy Terrel at Numfocus NumFOCUS currently represents 26 sponsored and 24 affiliated open scientific coding projects. Glancing at them from a distance, one might have to squint a bit to see a pattern emerge. In truth, the community doesn’t mind that at all, out of the variety comes innovation. Beyond the logos and stickers, what is this community actually doing? I present the various projects and argue that we have inadvertently created one of the most successful data science platforms in existence. From this vantage point, I pose some tough questions the community needs to answer: How can we present that platform more fully? How should we organize ourselves to make our work more valuable? How do we avoid a collapse of our communities?
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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    Just Ask : Designing intent driven algos (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 26 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Anna Schneider, Data Science Manager at Stitch Fix Classic recommender systems are great for answering the question “what does a user want in general?”. However, they only get you partway to an answer to “what does a user want right now?”. To close the gap, it helps to capture and act on real-time user intent. I’ll share two examples of this paradigm, and the resulting changes to our algorithms and architectures at Stitch Fix.
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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    Fraud Prevention from the Ground up (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 24 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Jason Dolatshahi – Director of Data Science at Stash Stash is the digital platform for saving & investing that promises financial inclusion for all. When we launched our checking account at the end of last year, we already had millions of customers, but we were about to make first contact with a formidable new foe: bank fraud. As a data science team, how do you develop and deploy a model when the dimensions of the problem are brand new and changing quickly? How do you ensure your stakeholders have the information they need to manage the liability risk to the business? How do you keep the user experience delightful while keeping out bad actors? Come find out!
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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    Data Science Conde Nast AI Infrastructure and Applications (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 30 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Sriram Subramanian - Head of Data Sciences at Condé Nast At Conde Nast, we have several AI/ML solutions spanning multiple business areas of the company: advertising, subscriptions, audience engagement and personalization. These solutions use different methodologies, software libraries and run in an automated manner. To manage all of this, we have developed our own purpose built AI infrastructure to support enterprise wide ML/AI applications. We will also cover a couple of applications that leverage this infrastructure and their business impact.
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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    Azure Networking Fundamentals : A Baseline for Understanding Networking in the Cloud (2019)
    [Erscheinungsort nicht ermittelbar] : Apress | Boston, MA : Safari
    Details
    ISBN: 9781484255667
    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 2 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: This video provides you with a baseline understanding of Azure Networking. It begins with an introduction to the high-level architecture of Azure Virtual Networks so that you can become familiar with the core capabilities, concepts, and settings of this technology. From there you will gain a basic understanding of firewall security, and discover how to leverage it using Network Security Groups and Application Security Groups. Then it is on to an overview of Azure load balancing services, including Azure Load Balancer, Azure Traffic Manager, and Front Door. Finally, you will learn about VPN Gateways and how they facilitate Azure VNet-to-VNet communication, as well as hybrid connectivity between on-premises and Azure networks. Networking is the cornerstone of any data center. While it is not entirely different in a cloud environment like Azure, you will discover that building a cloud networking stack also has its own eccentricities. For example, you will no longer be managing the physical layer, and not all services are available the same way as on-premises. All these quirks are covered in this video. After viewing Azure Networking Fundamentals you will be ready to get started in building and deploying your own enterprise-ready networking designs in Azure and/hybrid networking scenarios. What You Will Learn Gain a high-level view of Azure networking services and features and how to deploy them See new features including Azure Firewall and Azure Front-Door Protect and secure cloud applications in IAAS and PAAS. Follow along with to-the-point demos; learn by doing Apply the exact steps as guidelines in your own Azure environment Who This Video Is For IT professionals, system architects, cloud administrators, solution architects, and anyone who wants to learn about deploying infrastructure as a service in Azure public cloud. Having a base understanding of IPv4 and IPv6, networking concepts, firewalling, routing, load balancing, DNS, and IP addressing is beneficial.
    Note: Online resource; Title from title screen (viewed November 6, 2019)
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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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    Applied machine learning in finance - 2019 Artificial Intelligence Conference, New York (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 45 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) demonstrates how to apply machine learning techniques in quantitative finance, covering use cases involving both structured and alternative datasets. The focus of the talk will be on promoting reproducible research (through Jupyter notebooks and interactive plots) and interpretable models. 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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    Exam MD-100 Windows 10 (Video) (2019)
    [Erscheinungsort nicht ermittelbar] : Microsoft Press | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 8 hr., 12 min.)
    Edition: 1st edition
    Keywords: Microsoft Windows (Computer file) Study guides Examination ; Electronic data processing personnel Certification ; Electronic videos ; local ; Microsoft Windows (Computer file) ; Electronic data processing personnel ; Certification ; examination study guides ; Study guides ; Study guides ; Guides de l'étudiant
    Abstract: More than 8 hours of video instruction to help you support your organization’s Windows 10 deployment and prepare for Exam MD-100 Windows 10, one of the exams required to achieve Microsoft 365 Certified: Modern Desktop Administrator Associate. Overview This engaging, self-paced instructional video course demonstrates various aspects of deploying, maintaining, and securing Windows 10 devices and data. You learn methods and technologies that help you install and configure Windows 10, develop device management policies, protect data, improve security, configure networking, and more. If you’re planning to take Exam MD-100 Windows 10, this video course covers the exam objective domains published by Microsoft in a logical way for learning the technology and preparing for the exam. Throughout each lesson, Microsoft certified trainer and technical author Andrew Warren describes key concepts and puts them into action with demonstrations and real-world scenarios. You can follow along by building a test lab using virtual machines. About the Instructor Andrew Warren has more than 30 years of experience in the IT industry, many of which he has spent teaching and writing. He is a Microsoft Certified Trainer and has been involved as a subject matter expert in many of the Windows Server 2016 courses and as the technical lead in many Windows 10 courses. He also has been involved in developing TechNet sessions about Microsoft Exchange Server. He is the co-author of Exam Ref MD-100 Windows 10 and Exam Ref MD-101 Managing Modern Desktops and the author of Exam Ref 70-741 Networking with Windows Server 2016 and Exam Ref 70-742 Identity with Windows Server 2016 , published by Microsoft Press. Andrew is based in the United Kingdom and lives in rural Somerset, where he runs his own IT training and education consultancy. Skill Level Intermediate Learn How To Deploy Windows Manage devices and data Configure connectivity Maintain Windows Who Should Take This Course IT professionals who deploy, configure, secure, manage, and monitor devices and client applications in an enterprise environment IT professionals who manage identity, access, policies, updates, and apps IT professionals who want to explore new and updated features in Windows 10 Windows 10 administrators preparing for Exam MD-100 Windows 10 Course Requirements Foundational IT skills Basic understanding of and experience with Windows networking
    Note: Online resource; Title from title screen (viewed September 12, 2019)
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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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    O'Reilly Velocity Conference 2019 - Berlin, Germany (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    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 Artificial Intelligence Conference 2019 - San Jose, California (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    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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    On microservices, bounded contexts, and everything in between (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 43 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: “Ninety-five percent of the words are spent extolling the benefits of ‘modularity’ and that little, if anything, is said about how to achieve it”—Glenford J. Myers, 1978. The above quote is 40 years old. Today, four decades later, nothing has changed except terminology. Time to fix this. Vladik Khononov (Invesus Group) explains how to decompose a system into loosely coupled components: how to draw boundaries between services, how to decide whether some logic belongs to one service or another, and how domain-driven design can help us make those decisions. Finally, he takes a stab at answering the age-old question of what part of a microservice should be “micro” and how it can be measured. You’ll hear about neither Docker nor Kubernetes. Actually, nothing related to infrastructure. Instead, you’ll dive into the difference between microservices and bounded contexts, discover when each pattern should be used, and get takeaways from Vladik’s experience optimizing microservices-quotebased architectures at Naxex. 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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    Monolith to Microservices (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    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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    Introducing Azure Digital Twins : IoT Device Integration in Digital and Physical Spaces (2019)
    [Erscheinungsort nicht ermittelbar] : Apress | Boston, MA : Safari
    Details
    ISBN: 9781484253755
    Language: English
    Pages: 1 online resource (1 video file, approximately 37 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Create reusable, scalable, and spatially concise models of smart buildings that connect data across the physical and digital world using this video. For example, using Azure Digital Twins, you can define the location of offices at your place of business. Inside each office there are IoT devices with specific sensors (for example for temperature or lights). You can assign users to each room, so you have a clear view of the distribution of people in the office. This video begins with a gentle introduction to the Azure Digital Twins service, offering an overview and discussion of the key concepts related to it. From there you will progress through data processing and user-defined functions and learn about real IoT device integration with Azure Digital Twins. You will learn about Azure Digital Twins object models and spatial intelligence graph. In this new era of smart buildings, this video enables you to visualize comprehensive virtual representations of physical environments and all the associated devices, sensors, and people within it. You will be able to create definitions of spaces and combine them together with information about connected devices and sensors so that you can manage and implement resources with precision. What You Will Learn Create new Azure Digital Twins service instances Understand Azure Digital Twins object models and spatial intelligence graphs Work with data processing and user-defined functions Quickly connect IoT devices to Azure Digital Twins and create space definitions Discover routing events and messages Look at the limitations and additional resources for implementing solutions Who This Video Is For This video is for specialists, developers, and architects who are tasked with creating smart building solutions.
    Note: Online resource; Title from title screen (viewed August 19, 2019)
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    Game engines and machine learning (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: 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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    Deep learning for time series data (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: Arun Kejariwal (Independent) and Ira Cohen (Anodot) share a novel two-step approach for building more reliable prediction models by integrating anomalies in them. The first step uses anomaly detection algorithms to discover anomalies in a time series in the training data. In the second, multiple prediction models, including time series models and deep networks, are trained, enriching the training data with the information about the anomalies discovered in the first step. Anomaly detection for individual time series is a necessary but insufficient step due to the fact that anomaly detection over a set of live data streams may result in anomaly fatigue, thereby limiting effective decision making. One way to address the above is to carry out anomaly detection in a multidimensional space. However, this is typically very expensive computationally and hence not suitable for live data streams. Another approach is to carry out anomaly detection on individual data streams and then leverage correlation analysis to minimize false positives, which in turn helps in surfacing actionable insights faster. They then walk you through marrying correlation analysis with anomaly detection, discuss how the topics are intertwined, and detail the challenges you may encounter based on production data. They also showcase how deep learning can be leveraged to learn nonlinear correlation, which in turn can be used to further contain the false positive rate of an anomaly detection system. 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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    Choreographing microservices (San Jose, CA) (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    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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    Using Deep Learning to Build a Unified E-commerce Marketplace (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 19 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Ali Vanderveld, Director of Data Science at ShopRunner ShopRunner is an e-commerce company that receives feeds of product data from over 100 different retailer partners, including large department stores and retailers that specialize in electronics, appliances, nutritional products, and more. In order to provide a great user experience on our website and in our mobile app, we need to have one easy-to-navigate product taxonomy. We also would like to have sets of attribute tags that make it easy to filter down to exactly what any shopper is looking for. In this talk I will describe how we are using computer vision and natural language processing to place all of the products from our retailer partners into one easy-to-navigate shopping experience.
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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  • 74
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    Privacy and Algorithmic Fairness (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 30 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Manojit Nand – Senior Data Scientist at JPMorgan Chase & Co. Understanding how algorithms can reinforce societal biases has become an important topic in data science. Recent work for auditing models for fairness often requires access to potentially sensitive demographic information, placing algorithmic fairness in conflict with individual privacy. For example, gender recognition technology struggles to recognize the gender of transgender individuals. To develop more accurate models, we require information that could “out” these individuals, putting their social, psychological, and physical safety at risk. We will discuss social science perspectives on privacy and how these paradigms can be incorporated into statistical measures of anonymity. I will emphasize the importance of ensuring safety and privacy of all individuals represented in our data, even at the cost of model fairness.
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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  • 75
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    Machine Learning and Data Monetization (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 31 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Robert Welborn
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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  • 76
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    Personalization at Scale with AI (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 21 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Ayan Bhattacharya - Advanced Analytics Specialist Leader, Deloitte Consulting Conversational AI is the application of a combination of AI and cognitive services including Natural Language Processing, Speech Recognition and Intent Classification. It is focused on bringing voice, chat, and personal assistant technologies to intelligently automate human and technology interactions and improve client’s business outcomes as well as engagement with customers. There are varying levels of complexity in the virtual agents or chatbots; some are designed for answering common questions while others have a more complex architecture which includes the ability to disambiguate complex dialog and integrate with machine learning algorithms. The current marketplace for Conversational AI is being driven by cloud enabled platforms such as AWS, GCP, Azure and Watson; and there are over 2000 companies that have started developing their own niche industry solutions.
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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  • 77
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    Apply Natural Language Processing in Segmenting Online Audience (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 13 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Jasmine Ngo, Mgr, Analytics & Marketing Science at Deutsch Sometimes, conversations on social media don’t reflect the mass’ sentiments accurately (think about people who rarely use Twitter or have a public profile on Facebook). That’s when local news come into play – local articles can sometimes reflect sentiments on certain topics by specific areas. By scraping thousands of articles online and using NLP / other methodologies to analyze them, we can get interesting insights on different topic. This talk introduces a tool to do that.
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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  • 78
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    The Care and Feeding of Data Scientists (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | 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: Presented by Michelangelo D’Agostino, VP of Data Science & Engineering at ShopRunner Data scientists are hard to hire. But too often, companies struggle to find the right talent only to make avoidable mistakes that cause their best data scientists to leave. From organizational structure and leadership considerations to tooling and infrastructure to avoiding FOMO through continuing education, I’ll share concrete (and inexpensive) tips for keeping your data scientists engaged, productive, and performing their best for your business.
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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  • 79
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    Operationalize ML by Empowering People (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 29 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Jeff Sharpe – Manager / Master Software Engineer at Capital One Niraj Tank – Sr. Manager, Software Engineering at Capital One We have been working on operationalizing ML for past few years at CapitalOne Bank and would like to share our experiences and lessons we learned in building an ML platform, in our talk we plan to cover: — Self-Service for Data Scientists — Treat models, policies & features as content, not software, and allow live updates to content — Provide software engineering best practices to ML content(s) — How to meet enterprise need at scale — Lightweight services — Re-use models, data, and business logic wherever possible — Containerize software to simplify scaling — Multi-layer abstractions — Respond to real time events — Keep data in close proximity — Focus on low-latency communication and fast computations — Architect high-reliability services Some of the questions this session intend to answer: – Every FinTech enterprise needs to operationalize ML but most of them don’t know where to start, how to deliver and more importantly what not to do? – What architecture choices to explore and what tools to build to satisfy demanding needs of a thriving data science organization. – How can you build ways to include data scientists in the agile development process, leveraging their expertise in feature engineering while enabling them to take part in DevOps practices without needing full DevOps experience.
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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  • 80
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    Product(ive) Data Science (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 26 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Julie Hollek, Sr Data Scientist at Twitter Data scientists are the people behind the scenes, helping others deliver better, smarter results in their daily work. This is especially true for product data scientists who must hone their craft to determine what things are working for a given product, where do we want to take it next, and how can we make product decisions aligned with company is trying to build? Cross-functional communications are critical to success in this role; you need to be able to craft a message that is born out of math to make compelling arguments that are digestible by stakeholders across the business. In this session, we’ll define Product Data Science and discuss contributing factors to success.
    Note: Online resource; Title from title screen (viewed February 21, 2019) , Mode of access: World Wide Web.
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  • 81
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    How I Learned to Stop Worrying and Love Graph Databases (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 20 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Michael Zelenetz – Analytics Project Leader at New York-Presbyterian Hospital Healthcare data is highly connected but often lives in silos. Graph databases are promising emerging technologies for working with highly connected data. This talk will introduce data scientists to Neo4j—the leading graph database—and will discuss a proof of concept implementation at New York Presbyterian and will demonstrate some of the network analyses we were able to do as a result. This talk will be developer/data scientist focused and will include code snippets. We will introduce the graph data model and loading data into the database. We will discuss the pros and cons of graph databases. We will finish off with some practical examples from out proof of concept including community detection algorithms, using centrality to find providers who may be spreading infections, and examining physician referral patterns. Participants will leave being able to describe a graph database. They should be able to identify situations that may benefit from implementing a graph database. Finally, they should be able to create a simple graph model.
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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  • 82
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    Data and AI for Emerging Platforms (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 27 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Kabir Seth - VP Machine Learning & AI Strategy, Wall Street Journal & Alex Siegman - AI Technical Program Manager, Dow Jones Walking through the steps necessary to appropriately leverage AI in a large organization, including tips and tricks for identifying business opportunities that lend themselves to AI, as well as best practices for each step of the AI project management process, all while navigating complex organizational structures.
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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  • 83
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    Automated Feature Engineering (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 18 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Namita Lokare Feature engineering plays a significant role in the success of a machine learning model. Most of the effort in training a model goes into data preparation and choosing the right representation. In this talk, I will focus on a robust feature engineering method, Randomized Union of Locally Linear Subspaces (RULLS). We generate sparse, non-negative, and rotation invariant features in an unsupervised fashion. RULLS aggregates features from a random union of subspaces by describing each point using globally chosen landmarks. These landmarks serve as anchor points for choosing subspaces. Our method provides a way to select features that are relevant in the neighborhood around these chosen landmarks. Distances from each data point to k closest landmarks are encoded in the feature matrix. The final feature representation is a union of features from all chosen subspaces. The effectiveness of our algorithm is shown on various real-world datasets for tasks such as clustering and classification of raw data and in the presence of noise. We compare our method with existing feature generation methods. Results show a high performance of our method on both classification and clustering tasks.
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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  • 84
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    Ad Planning & Operations : Predictive Analytics for Resource Allocation (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 28 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Leondra James, Mgr, Analytics & Operations at Saatchi & Saatchi Saatchi & Saatchi is global, full service advertising agency / creative communications network. Learn about the interesting questions they’re asking and how they’re leveraging data to answer them. Entails broad overview of predicting advertising initiative resources and their respective allocations.
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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  • 85
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    Literate Statistical Programming is not Just About Reproducibility (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 29 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by John Peach, Sr Data Scientist at Amazon Alexa Science is facing a crisis around reproducibility and data science is not immune. Literate Statistical Programming is a workflow that binds the code used in an analysis to the interpretation of the results. While this creates reproducibility it also addresses issues around, auditing, re-usability and allows for rapid iteration and experimentation. This talk will describe a workflow that I have successfully used on small-scale data-sets in start-ups and on Amazon-scale problems in my work on Alexa. The talk will cover the tooling, workflow, and the philosophy you need to master Literate Statistical Programming.
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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  • 86
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    Improving the Worlds Largest Online Grocery Catalog : A Data Science Story (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 28 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Ishant Nayer, Sr Data Scientist at Instacart Being a data-driven company, Instacart realizes the power of good quality data. While trying to maximize the efficiency of data consumption by all work streams such as recommendation systems and availability systems, we are trying to make our Catalog the best in the world by delivering precise information to all our end-users including shoppers and consumers. This session will cover the following areas: 1. How we used data science to auto-detect inconsistencies in the data attributes of millions of items comprising the Catalog, in real-time. 2. How we defined and utilized North Star metrics to optimize data quality of our Catalog 3. Different approaches being used to deliver a great customer experience.
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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  • 87
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    Search Engine in Startups : What to Optimize (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 28 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Liang Wu, Machine Learning Data Scientist at Airbnb Choosing the correct optimization metric is key to success of a search engine. Unlike in traditional web searches, where clicks are clearly the main objective to optimize, many emerging vertical search engines like E-Commerce search may require a different optimization metric, such as conversions, revenue, and quality. Selection of a good metric may depend on the query type (transactional vs. navigational vs. informational) and also on the goal of a business (profitability vs. growth). For example, a typical product search engine may focus on maximizing the number of transactions and total revenue, while navigational search may aim at minimizing the total number of clicks. In this talk, we will investigate factors needed to be considered when we are in search for a good metric, and we will also walk through an example of designing an optimization metric for a particular business, including how it is selected, mathematically defined, and optimized with a machine learning framework.
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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  • 88
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    The Tabloid Proteome : Orthogonal use of public proteomics data to derive biologically related protein network (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 19 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Surya Gupta – Postdoctoral Researcher at VIB-UGent Mass-spectrometry based proteomics experiments produces large amounts of data. While typically acquired to answer specific biological questions, these data can also be reused in orthogonal ways to reveal biological knowledge. We have developed a novel method for such orthogonal data reuse of public proteomics data to detect biologically associated protein pairs. Mass-spectrometry proteomics experiments were obtained and reprocessed from the PRIDE database. For the identified proteins, we calculated the co-occurrence score, using Jaccard similarity. Protein pairs with score of atleast 0.4 were mapped to five knowledgebases; Reactome, Ensembl, IntAct, BioGRID, and CORUM, to assign potential biological relevance. Of the 2325 protein pairs that pass the Jaccard similarity threshold, we 81% of protein pairs with biological annotation (68% with five knowledgebases and 13% with GO terms). While comparison with randomly selected protein pairs, less than 2% protein pairs were found to be annotated. Furthermore, to extend the usability and accessibility of the detected protein pairs for research community, an online database called Tabloid Proteome was established. Our approach shows that by re-using publically available data in a fully orthogonal way, effectively treating these data as a proteome-wide association study, we can extract various biologically meaningful patterns, which moreover, were quite complementary to associations detected by established protein-protein interaction techniques. Additionally, Tabloid Proteome features a simple yet powerful web interface that allows fast and easy access to all these protein associations, with their possible biological annotation.
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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  • 89
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    Interpretable Predictive Models in the Healthcare Domain (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 32 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Sridharan Kamalakannan, Head of Data Science at Humana Predictive models are often used to identify individuals that will likely have escalating health severity in the future and accordingly deliver appropriate interventions. However, for the clinicians and care managers, these predictive models often act as a black-box at an individual level. The reason for this being, typically predictive models use combinations of complicated algorithms that makes it hard to explain the reason behind a predictive model score at an individual level. This talk will focus on model and feature agnostic methodologies and techniques that help uncover the drivers behind a prediction at a personal level in a healthcare setting.
    Note: Online resource; Title from title screen (viewed February 21, 2019) , Mode of access: World Wide Web.
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  • 90
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    Enabling Better Shopping Experiences Using Technology, Data, & Fashion Attributes (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 29 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Rhonda Textor, Head of Data Science at True Fit Recent advances in technology such as computer vision, deep learning, and recommender systems are being used to enable new shopping experiences. Examples include visual search, recommending similar items, and recommending items that other shoppers also viewed. However, technology alone without an understanding of shoppers, fashion, and retail falls short of solving shopping recommendation problems. We at True Fit believe that details matter, especially for modeling individual fashion preferences. Because of that, we have built the largest fashion and retail dataset called the Fashion Genome. In this talk, I will share some insights we have gained from the Fashion Genome that have influenced our approach to building fashion recommendation systems. I will also show how we leverage the fashion details of products, i.e., our Fashion Attributes, to combine fashion and technology to make great recommendations. Finally, I will share how we leverage our large dataset and cutting edge technology to enable personalized shopping experiences.
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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  • 91
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    Challenges in Machine Learning from Model Building to Deployment at Scale (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 19 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Anupama Joshi Companies are moving towards AI/Machine learning very fast. Data scientist are building models and training models. But challenges come when deploying models in production. How to maintain multiple models? Creating a common platform that allows model management and deployment easily and reliably is becoming a necessity for organizations to accelerate product development. In this talk, I will talk about the challenges faced and the solutions used to make this process easy.
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  • 92
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    Algorithmic Recommendations at The New York Times (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 27 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Anna Coenen Algorithmic curating at the Times brings many unique challenges. We want our recommendations to feel personal and relevant, but not creepy. We want articles to be timely, yet also showcase older pieces that our readers still enjoy. We want to increase engagement, but without sacrificing editorial judgment. This talk describes how we achieved these goals through a combination of Machine Learning, experimentation, and diligent editorial curation.
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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  • 93
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    Deep Learning Applications in the Biosciences (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 21 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Charles Alcorn – Head of Data Science at Roche Molecular Systems Oncology diagnostics and treatment is a rapidly changing field of medicine with new advancements announced almost daily. The number of diagnostic tests to select treatments based on a patient’s unique genetic mutations and tumor pathology characteristics has grown, as have the number of therapies available. These therapies can be matched to a patient’s likelihood to respond to treatment based on the results from diagnostic tests. Estimates indicate that Oncologists would have to read the literature continuously around the clock 365 days a year to maintain their knowledge of new diagnostic tests and treatments. Further, diagnostic testing and treatment as well as associated treatment guidelines vary by patient population and country. This talk will describe medical content management concepts for the field of Oncology including data architecture, data curation, adopting to differing-and-ever-changing treatment guidelines, capture of up-to-date regulatory information, and country-specific examples. The roadmap that we are developing to support Clinical Decision Support Software in a Global Marketplace for our products and services will be described.
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  • 94
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    The AI Knobs, Tips and Tricks to Jumpstart AI projects (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 30 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Anusua Trivedi, Sr Data Scientist Lead, AI for Good at Microsoft AI serves the purpose of enabling human beings in making better decisions. In this session, we talk about how the actions of AI are the result of the human inputs going into its programming. We talk about how an AI’s bias is not its own, but the human bias with which it has been programmed. We emphasize the choice of the right metric and the type of data used for testing and training to avoid such bias. We discuss the need to understand the dependence between the data used and the models employed and optimize only areas that matter. We discuss how to focus on feature engineering and be thoughtful about the ethics of ML applications. Other issues such as the need for regulations and other considerations within it that require deliberation are also touched upon.
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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  • 95
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    A Product Development Approach to Improving Data Quality (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 27 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Dalela Bharati – Product Owner, Data & Analytics at Booking.com Poor data quality (DQ) is crippling to any data scientist. Especially organisation wide complex DQ challenges for fundamental datasets that can take months to fix. This talk/ session outlines the product development approach we adopted to solving a DQ challenge at Booking.com
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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  • 96
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    AI and ML for the Data Quality of Clinical Trial Studies (2019)
    [Erscheinungsort nicht ermittelbar] : Data Science Salon | Boston, MA : Safari
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    Language: English
    Pages: 1 online resource (1 video file, approximately 27 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Presented by Hemalatha B Raju – Lead Data Scientist at Biorasi Running a clinical trial is always very complex. But with the implementation of machine learning we can significantly improve the efficiency of clinical trial development. Machine learning logic and algorithms can help us advance the patient selection process for clinical trials, improve the data quality, reduce the time and cost in the execution of clinical trials. for accurate predictions of outcomes using pattern recognition. Machine learning algorithms could be potentially applied to develop comprehensive risk-based monitoring tools, fraud detection pipeline, on-study analytics models and solutions for various clinical trials that alerts the clinical monitors and the pharmaceutical companies about the quality of clinical sites . Clinical data can also be reviewed at aggregate level regularly throughout assigned studies using analytical reporting tools to support the identification of risks and data trends. The rules-based logic could be used throughout the clinical trial studies to analyze the primary and secondary endpoints, required for the safety and efficacy analysis of the investigational drug and thus improve the efficiency of clinical trial studies.
    Note: Online resource; Title from title screen (viewed September 10, 2019) , Mode of access: World Wide Web.
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  • 97
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    Online Resource
    Choreographing microservices (NY) (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 1 hr., 29 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 New York.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
    URL: lizenzpflichtig
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  • 98
    Online Resource
    Online Resource
    AWS Certified Machine Learning-Specialty (ML-S) (2019)
    [Erscheinungsort nicht ermittelbar] : Pearson IT Certification | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 5 hr., 38 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: More Than 7 Hours of Video Instruction Overview This course covers the essentials of Machine Learning on AWS and prepares a candidate to sit for the AWS Machine Learning-Specialty (ML-S) Certification exam. Four main categories are covered: Data Engineering, EDA (Exploratory Data Analysis), Modeling, and Operations. Description This 7+ hour Complete Video Course is fully geared toward the AWS Machine Learning-Specialty (ML-S) Certification exam. The course offers a modular lesson and sublesson approach, with a mix of screencasting and headhsot treatment. Data Engineering instruction covers the ingestion, cleaning, and maintenance of data on AWS. Exploratory Data Analysis covers topics including data visualization, descriptive statistics, and dimension reduction and includes information on relevant AWS services. Machine Learning Modeling covers topics including feature engineering, performance metrics, overfitting, and algorithm selection. Operations covers deploying models, A/B testing, using AI services versus training your own model, and proper cost utilization. The supporting code for this LiveLesson is located at http://www.informit.com/store/aws-certified-machine-learning-specialty-ml-s-complete-9780135556511 . About the Instructor Noah Gift is a lecturer and consultant at both the UC Davis Graduate School of Management MSBA program and the Graduate Data Science program, MSDS, at Northwestern. He teaches and designs graduate machine learning, AI, data science courses, and consulting on machine learning and cloud architecture for students and faculty. These responsibilities include leading a multi-cloud certification initiative for students. Noah is a Python Software Foundation Fellow, AWS Subject Matter Expert (SME) on Machine Learning, AWS Certified Solutions Architect, AWS Academy accredited instructor, Google Certified Professional Cloud Architect, and Microsoft MTA on Python. Noah has published close to 100 technical publications including two books on subjects ranging from cloud machine learning to DevOps. Noah received an MBA from UC Davis, a M.S. in Computer Information Systems from Cal State Los Angeles, and a B.S. in Nutritional Science from Cal Poly San Luis Obispo. Currently he consults for startups and other companies on machine learning, cloud architecture, and CTO-level consulting as the founder of Pragmatic AI Labs. His most recent publications are Pragmatic AI: An introduction to Cloud-Based Machine Learning (Pear...
    Note: Online resource; Title from title screen (viewed February 28, 2019)
    URL: lizenzpflichtig
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  • 99
    Online Resource
    Online Resource
    Artificial Intelligence Conference 2019 - New York, New York (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 75 hr., 47 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: Why did companies like Intuit, JP Morgan Chase, MasterCard, and BuzzFeed deploy AI and what business advantages have they already reaped from those deployments? How have the toolsets recently developed at Google (BERT) and Microsoft (Project Brainwave) opened up AI as a mainstream business reality? How does IBM's AI Fairness 360 toolkit combat the very real problem of unwanted bias in AI applications? You'll find the answers to these questions and many more in this video compilation of the best talks from AI New York 2019. Containing hours of material to explore at your own pace, this video compilation provides an insider's view of the latest developments in AI. Highlights include:M/p〉 Complete video recordings of the talks delivered at AI NY 2019 by 170 of the world's top AI experts. Keynote addresses from AI's best thinkers, such as MIT's Aleksander Madry, Intuit's Desiree Gosby, Princeton University's Olga Troyanskaya, Netflix's Tony Jebara, Stanford University's Christopher Ré, Facebook's Kim Hazelwood, Carnegie Mellon University's Martial Hebert, and Primer's Sean Gourley, plus a look at Dell's "Sophia", the world’s first robot citizen. All of the Executive Briefings and detailed case studies from the exclusive AI Business Summit, including Kristian Hammond's (Northwestern Computer Science) day long tutorial offering a practical framework for bringing AI into your company; Adam Cheyer's (Samsung) look at how AI enables a totally new form of software development where humans and machines work collaboratively together; and Jennifer Fernick's (NCC Group) learned predictions of the industries that will benefit from the coming intersection of quantum computing, machine learning, and AI. Tutorials by AI's most experienced practitioners, including Gunnar Carlsson (Stanford University) on using topological data analysis to understand, build, and improve neural networks; Bruno Goncalves (JPMorgan Chase) on using recurrent neural networks for time series analysis; and Mo Patel (Independent) on how to build machine learning models in PyTorch. Sessions focused on machine learning, including Alina Matyukhina's (Canadian Institute for Cybersecurity) reveal of the methods dishonest actors use ML to mimic the coding style of software developers in open source projects; Chakri Cherukuri's (Bloomberg LP) discussion of how to apply machine learning and deep learning techniques in quantitative finance; and Cibele Montez Halasz's (Twitter) description of time...
    Note: Online resource; Title from title screen (viewed April 17, 2019)
    URL: lizenzpflichtig
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  • 100
    Online Resource
    Online Resource
    7 years of DDD : Tackling complexity in large-scale marketing systems (2019)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (1 video file, approximately 49 min.)
    Edition: 1st edition
    Keywords: Electronic videos ; local
    Abstract: It turns out that domain-driven design is not just for cargo shipping. Vladik Khononov (Naxex) explains how he and his team embraced domain-driven design (DDD) (with very limited resources and a very short time to market) at Plexop, a large-scale marketing system that spans over a dozen different business domains. Join in to learn how DDD allowed the team to manage business complexities, find out strategies for defining context boundaries, explore lessons learned the hard way, and discover where they had to adapt the DDD methodology to fit the company’s needs. This session was recorded at the 2019 O'Reilly Software Architecture Conference in New York.
    Note: Online resource; Title from title screen (viewed October 31, 2019)
    URL: lizenzpflichtig
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