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  • 1
    Online Resource
    Online Resource
    Essential Math for AI (2023)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (54 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local ; Electronic books
    Abstract: Companies are scrambling to integrate AI into their systems and operations. But to build truly successful solutions, you need a firm grasp of the underlying mathematics. This accessible guide walks you through the math necessary to thrive in the AI field such as focusing on real-world applications rather than dense academic theory. Engineers, data scientists, and students alike will examine mathematical topics critical for AI--including regression, neural networks, optimization, backpropagation, convolution, Markov chains, and more--through popular applications such as computer vision, natural language processing, and automated systems. And supplementary Jupyter notebooks shed light on examples with Python code and visualizations. Whether you're just beginning your career or have years of experience, this book gives you the foundation necessary to dive deeper in the field. Understand the underlying mathematics powering AI systems, including generative adversarial networks, random graphs, large random matrices, mathematical logic, optimal control, and more Learn how to adapt mathematical methods to different applications from completely different fields Gain the mathematical fluency to interpret and explain how AI systems arrive at their decisions
    Note: Online resource; Title from title page (viewed February 25, 2023) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 2
    Online Resource
    Online Resource
    Data Science on the Google Cloud Platform, 2nd Edition (2023)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (166 pages)
    Edition: 2nd edition
    Keywords: Electronic books
    Abstract: Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build using Google Cloud Platform (GCP). This hands-on guide shows data engineers and data scientists how to implement an end-to-end data pipeline, using statistical and machine learning methods and tools on GCP. Through the course of this updated second edition, you'll work through a sample business decision by employing a variety of data science approaches. Follow along by implementing these statistical and machine learning solutions in your own project on GCP, and discover how this platform provides a transformative and more collaborative way of doing data science. You'll learn how to: Employ best practices in building highly scalable data and ML pipelines on Google Cloud Automate and schedule data ingest using Cloud Run Create and populate a dashboard in Data Studio Build a real-time analytics pipeline using Pub/Sub, Dataflow, and BigQuery Conduct interactive data exploration with BigQuery Create a Bayesian model with Spark on Cloud Dataproc Forecast time series and do anomaly detection with BigQuery ML Aggregate within time windows with Dataflow Train explainable machine learning models with Vertex AI Operationalize ML with Vertex AI Pipelines
    Note: Online resource; Title from title page (viewed January 25, 2023) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 3
    Online Resource
    Online Resource
    Machine Learning with Apache Spark (2023)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (75 pages)
    Edition: 1st edition
    Keywords: Electronic books
    Abstract: Advances in machine learning techniques, the cloud, and the ability to leverage hardware acceleration have changed the way we work with data — adding entirely new capabilities and business models to the mix. But the demand for processing training data has outpaced the increase in computation power. This practical and comprehensive guide will show you how to distribute your machine learning workload across multiple machines and turn centralized systems into distributed ones. Machine Learning with Spark examines various technologies for building end-to-end distributed machine learning platforms based on the Apache Spark ecosystem with Spark MLlib, TensorFlow, Horovod, PyTorch, and more. This book shows you when to use each technology and why. You'll also learn how to: Build efficient parallelization of the training process Create a coherent model Leverage a set of open source tools to build scalable end-to-end ML platform Enable more advanced, tailor-made products Use distributed ML techniques to increase the quality of predictions and ML modules Design practical distributed machine learning systems
    Note: Online resource; Title from title page (viewed February 25, 2023) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 4
    Online Resource
    Online Resource
    Learning Ray (2023)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (66 pages)
    Edition: 1st edition
    Keywords: Electronic books
    Abstract: Get started with Ray, the open source distributed computing framework that greatly simplifies the process of scaling compute-intensive Python workloads. With this practical book, Python programmers, data engineers, and data scientists will learn how to leverage Ray locally and spin up compute clusters. You'll be able to use Ray to structure and run machine learning programs at scale. Authors Max Pumperla, Edward Oakes, and Richard Liaw show you how to build reinforcement learning applications that serve trained models with Ray. You'll understand how Ray fits into the current landscape of data science tools and discover how this programming language continues to integrate ever more tightly with these tools. Distributed computation is hard, but with Ray you'll find it easy to get started. Learn how to build your first distributed application with Ray Core Conduct hyperparameter optimization with Ray Tune Use the Ray RLib library for reinforcement learning Manage distributed training with the RaySGD library Use Ray to perform data processing Learn how work with Ray Clusters and serve models with Ray Serve Build an end-to-end machine learning application with Ray
    Note: Online resource; Title from title page (viewed April 25, 2023) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 5
    Online Resource
    Online Resource
    Deep learning (2023)
    [Erscheinungsort nicht ermittelbar] : Tecniche Nuove | Boston, MA : Safari
    Details
    ISBN: 9788848141130
    Language: English , Italian
    Pages: 1 online resource (264 pages)
    Edition: 1st edition
    Keywords: Electronic books ; local
    Abstract: Negli ultimi dieci anni, con il ritorno delle reti neurali, la comprensione del Deep Learning è diventata essenziale e questo manuale fornisce un’introduzione approfondita per i data scientist e gli ingegneri del software con precedenti esperienze nel machine learning. Inizierete con le basi del Deep Learning e passerete rapidamente ai dettagli di importanti architetture avanzate, implementando tutto da zero. L’autore Seth Weidman vi mostra come funzionano le reti neurali usando un approccio basato su principi primi. Imparerete come applicare da zero le reti neurali multistrato, le reti neurali convoluzionali e quelle ricorrenti. Acquisendo una comprensione dettagliata di come queste reti funzionino matematicamente, computazionalmente e concettualmente, porterete a termine con successo i vostri futuri progetti di Deep Learning.
    Note: Online resource; Title from title page (viewed September 21, 2023) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 6
    Online Resource
    Online Resource
    Alteryx Designer : The Definitive Guide (2023)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    ISBN: 9781098107499 , 1098107497
    Language: English
    Pages: 1 online resource (66 pages)
    Edition: 1st edition
    Parallel Title: Erscheint auch als
    DDC: 005.75/65
    Keywords: Database management Software ; Data mining Software ; Electronic books ; local ; Electronic books
    Abstract: Analytics projects are frequently long-drawn-out affairs, requiring multiple teams and skills to clean, join, and eventually turn data into analysis for timely decision-making. Alteryx Designer changes all of that. With this low-code, self-service, drag-and-drop workflow platform, new and experienced data and business analysts can deliver results in hours instead of weeks. This practical book shows you how to master all areas of Alteryx Designer quickly. Author and Alteryx ACE Joshua Burkhow starts with the basics of building a workflow, then introduces more than 200 tools for working with intermediate and advanced analytics functionality. With Alteryx Designer's all-in-one toolkit, you'll migrate from legacy analytics software or Excel with ease. Ready to work with data quickly and efficiently? This guide gets you started. Learn the fundamentals of cleaning, prepping, and analyzing data with Alteryx Designer Install, navigate, and quickly become competent with the Alteryx Designer layout and functionality Construct accurate, performant, reliable, and well-documented workflows that automate business processes Learn intermediate techniques using spatial analytics, reporting, and in-database tools Dive into advanced Alteryx capabilities, including predictive and machine learning tools Get introduced to the entire Alteryx Analytic Process Automation (APA) Platform
    Note: Online resource; Title from title page (viewed March 25, 2023) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 7
    Online Resource
    Online Resource
    Managing Cloud Native Data on Kubernetes (2023)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (90 pages)
    Edition: 1st edition
    Keywords: Electronic books
    Abstract: Kubernetes has become the primary platform for deploying and managing cloud native applications. But because it was originally designed for stateless workloads, working with data on Kubernetes has been challenging. If you want to avoid the inefficiencies and duplicative costs of having separate infrastructure for applications and data, this practical guide can help. Using Kubernetes as your platform, you'll discover open source technologies that are designed and built for the cloud. Delve into case studies to avoid the pitfalls others have faced and explore new use cases. Get an insider's view of what's coming from the innovators who are creating next-generation architectures and infrastructure. And you'll learn how to: Manage different data use cases on Kubernetes Reduce costs and simplify application development Leverage data and infrastructure to create new use cases and business models Make data infrastructure choices that are cost-efficient, secure, scalable, and elastic And more
    Note: Online resource; Title from title page (viewed January 25, 2023) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 8
    Online Resource
    Online Resource
    Building Solutions with the Microsoft Power Platform (2023)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (26 pages)
    Edition: 1st edition
    Keywords: Electronic books
    Abstract: With the accelerating speed of business and the increasing dependence on technology, companies today are significantly changing the way they build in-house business solutions. Many now use low-code and no code technologies to help them deal with specific issues, but that's just the beginning. With this practical guide, power users and developers will discover ways to resolve everyday challenges by building end-to-end solutions with the Microsoft Power Platform. Author Jason Rivera, who specializes in SharePoint and the Microsoft 365 solution architecture, provides a comprehensive overview of how to use the Power Platform to build end-to-end solutions that address tactical business needs. By learning key components of the platform, including Power Apps, Power Automate, and Power BI, you'll be able to build low-code and no code applications, automate repeatable business processes, and create interactive reports from available data. Learn how the Power Platform apps work together Incorporate AI into the Power Platform without extensive ML or AI knowledge Create end-to-end solutions to solve tactical business needs, including data collection, process automation, and reporting Build AI-based solutions using Power Virtual Agents and AI Builder
    Note: Online resource; Title from title page (viewed March 25, 2023) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 9
    Online Resource
    Online Resource
    Scaling Python with Ray (2023)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (38 pages)
    Edition: 1st edition
    Keywords: Electronic books
    Abstract: Serverless computing enables developers to concentrate solely on their applications rather than worry about where they've been deployed. With the Ray general-purpose serverless implementation in Python, programmers and data scientists can hide servers, implement stateful applications, support direct communication between tasks, and access hardware accelerators. In this book, authors Holden Karau and Boris Lublinsky show you how to scale existing Python applications and pipelines, allowing you to stay in the Python ecosystem while avoiding single points of failure and manual scheduling. If your data processing has grown beyond what a single computer can handle, this book is for you. Written by experienced software architecture practitioners, Scaling Python with Ray is ideal for software architects and developers eager to explore successful case studies and learn more about decision and measurement effectiveness. This book covers distributed processing (the pure Python implementation of serverless) and shows you how to: Implement stateful applications with Ray actors Build workflow management in Ray Use Ray as a unified platform for batch and streaming Implement advanced data processing with Ray Apply microservices with Ray platform Implement reliable Ray applications
    Note: Online resource; Title from title page (viewed June 25, 2023) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 10
    Online Resource
    Online Resource
    Learning Data Science (2023)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    Language: English
    Pages: 1 online resource (70 pages)
    Edition: 1st edition
    DDC: 004
    Keywords: Information technology ; Information retrieval ; Databases ; Data mining ; Electronic books
    Abstract: As an aspiring data scientist, you appreciate why organizations rely on data for important decisions--whether it's for companies designing websites, cities deciding how to improve services, or scientists discovering how to stop the spread of disease. And you want the skills required to distill a messy pile of data into actionable insights. We call this the data science lifecycle: the process of collecting, wrangling, analyzing, and drawing conclusions from data. Learning Data Science is the first book to cover foundational skills in both programming and statistics that encompass this entire lifecycle. It's aimed at those who wish to become data scientists or who already work with data scientists, and at data analysts who wish to cross the "technical/nontechnical" divide. If you have a basic knowledge of Python programming, you'll learn how to work with data using industry-standard tools like pandas. Refine a question of interest to one that can be studied with data Pursue data collection that may involve text processing, web scraping, etc. Glean valuable insights about data through data cleaning, exploration, and visualization Learn how to use modeling to describe the data Generalize findings beyond the data
    Note: Online resource; Title from title page (viewed May 25, 2023) , Mode of access: World Wide Web.
    URL: lizenzpflichtig
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  • 11
    Online Resource
    Online Resource
    Go Cookbook (2023)
    [Erscheinungsort nicht ermittelbar] : O'Reilly Media, Inc. | Boston, MA : Safari
    Details
    ISBN: 9781098122072 , 1098122070
    Language: English
    Pages: 1 online resource (25 pages)
    Edition: 1st edition
    Parallel Title: Erscheint auch als
    DDC: 005.13/3
    Keywords: Go (Computer program language) ; Open source software Programming ; Computer programming ; Electronic books ; Go (Langage de programmation) ; Logiciels libres - Programmation ; Programmation (Informatique) ; computer programming
    Abstract: Go is an increasingly popular language for programming everything from web applications to distributed network services. This practical guide provides recipes to help you unravel common problems and perform useful tasks when working with Go. Each recipe includes self-contained code solutions that you can freely use, along with a discussion of how and why they work. Programmers new to Go can quickly ramp up their knowledge while accomplishing useful tasks, and experienced Go developers can save time by cutting and pasting proven code directly into their applications. Recipes include: Creating a module; Calling code from another module; Returning and handling an error; Converting strings to numbers (or converting numbers to strings); Modifying multiple characters in a string; Creating substrings from a string; Capturing string input; And so much more.--Back cover
    Note: Online resource; Title from title page (viewed July 25, 2023) , Mode of access: World Wide Web.
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