Название: Deep Learning and Practice with MindSpore
Автор: Lei Chen
Издательство: Springer
Год: 2021
Формат: PDF
Страниц: 403
Размер: 14,1 Mb
Язык: English

This book systematically introduces readers to the theory of deep learning and explores its practical applications based on the MindSpore AI computing framework. Divided into 14 chapters, the book covers deep learning, deep neural networks (DNNs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), unsupervised learning, deep reinforcement learning, automated machine learning, device-cloud collaboration, deep learning visualization, and data preparation for deep learning. To help clarify the complex topics discussed, this book includes numerous examples and links to online resources.

Название: Software Architecture: The Hard Parts (Early Release)
Автор: Neal Ford, Mark Richards, Pramod Sadalage, and Zhamak Dehghani
Издательство: O’Reilly Media
Год: 2021-08-17: First release
Формат: ePUB
Страниц: 586
Размер: 11,5 Mb
Язык: English

Architects are often harried because they have no clean, easy decisions: everything is an awful tradeoff between two or more less than perfect alternatives. These are the difficult problems architects face, what this book's authors call "the hard parts." These topics have no best practices, forcing architects to understand various tradeoffs to succeed. This book discusses these hard parts by not only investigating what makes architecture so difficult, but also by providing proven ways to address these problems and make them easier. The book explores topics such as choosing an appropriate architecture, deciding on service granularity, managing workflows and orchestration, managing and decoupling contracts, managing distributed transactions, and optimizing operational characteristics such as scalability, elasticity, and performance. As practicing consultants, the authors focus on questions they commonly hear architects ask and provide techniques that enable them to discover the tradeoffs necessary to answer these questions.

Название: WPF: Windows Presentation Foundation в .NET 4.0 с примерами на C# 2010 для профессионалов
Автор: Мэтью Мак-Дональд
Издательство: СПб.: Вильямс
Год: 2011
Cтраниц: 1020
Формат: djvu
Размер: 13 мб
Язык: русский

В этой книге описано, как в действительности работает WPF. В ней предлагается деловой, практический подход, который способствует быстрому и простому построению высококачественных WPF-приложений. Вслед за основами рассматриваются более сложные аспекты WPF и их отношения с другими элементами платформы .NET 4.0 и связанными технологиями, такими как Silverlight.

Название: Enterprise AIOps: A Framework for Enabling Artificial Intelligence
Автор: Justin Neroda, Steve Escaravage, Aaron Peters
Издательство: O’Reilly Media, Inc.
Год: 2021-08-16
Страниц: 103
Язык: английский
Формат: pdf, epub
Размер: 10.1 MB

The mountains of data generated on a daily basis has vastly outstripped growth in the supply of technical analysts. How can your organization provide value from these data volumes with your existing analytical capabilities and staff? With this report, business leaders looking to move from small AI pilot projects to an enterprise-wide deployment will explore an AI operations engineering framework known as AIOps. When deployed effectively, Artificial Intelligence (AI) provides the necessary force multiplier, allowing organizations to generate insights not possible even a few years ago. AI provides organizations with the ability to process vast amounts of data by training algorithms to automate current processes, generate new insights, and then present these insights so that decision makers can act.

Название: Data Science at the Command Line, 2nd Edition
Автор: Jeroen Janssens
Издательство: O’Reilly Media, Inc
Год: 2021
Формат: ePUB
Страниц: 250
Размер: 10 Mb
Язык: English

This thoroughly revised guide demonstrates how the flexibility of the command line can help you become a more efficient and productive data scientist. You'll learn how to combine small yet powerful command-line tools to quickly obtain, scrub, explore, and model your data. To get you started, author Jeroen Janssens provides a Docker image packed with over 80 tools–useful whether you work with Windows, macOS, or Linux.

Название: Computational Methods for Engineers: Modeling, Algorithms and Analysis
Автор: J.P. Mmbaga, K. Nandakumar, R.E. Hayes, M.R. Flynn
Издательство: ALPHA Education Press
Год: 2021
Формат: PDF
Страниц: 335
Размер: 10.43 MB
Язык: English

Revolutionary advances in hardware and software technology have made computer aided design and analysis a standard tool in engineering practice. This obviously puts a lot of power in the hands of the end user, in order to use these tools wisely and interpret the results correctly, users are expected to have a sound knowledge of the relationship between the physical world and the mathematical model and that between the mathematical model and the numerical approximation.

Название: A Logical Theory of Causality
Автор: Alexander Bochman
Издательство: The MIT Press
Год: 2021
Страниц: 366
Язык: английский
Формат: epub
Размер: 10.1 MB

A general formal theory of causal reasoning as a logical study of causal models, reasoning, and inference. In this book, Alexander Bochman presents a general formal theory of causal reasoning as a logical study of causal models, reasoning, and inference, basing it on a supposition that causal reasoning is not a competitor of logical reasoning but its complement for situations lacking logically sufficient data or knowledge. Bochman also explores the relationship of this theory with the popular structural equation approach to causality proposed by Judea Pearl and explores several applications ranging from artificial intelligence to legal theory, including abduction, counterfactuals, actual and proximate causality, dynamic causal models, and reasoning about action and change in Artificial Intelligence (AI).

Название: Machine Learning, revised and updated edition
Автор: Ethem Alpaydin
Издательство: The MIT Press
Год: 2021
Формат: ePUB, PDF
Страниц: 280
Размер: 10 Mb
Язык: English

A concise overview of machine learning—computer programs that learn from data—the basis of such applications as voice recognition and driverless cars.
Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition—as well as some we don't yet use everyday, including driverless cars. It is the basis for a new approach to artificial intelligence that aims to program computers to use example data or past experience to solve a given problem. In this volume in the MIT Press Essential Knowledge series, Ethem Alpaydín offers a concise and accessible overview of "the new AI." This expanded edition offers new material on such challenges facing machine learning as privacy, security, accountability, and bias.

Название: Technical Debt in Practice: How to Find It and Fix It
Автор: Neil Ernst, Rick Kazman, Julien Delange
Издательство: The MIT Press
Год: 2021
Страниц: 288
Язык: английский
Формат: True EPUB
Размер: 12.8 MB

The practical implications of technical debt for the entire software lifecycle; with examples and case studies. Technical debt in software is incurred when developers take shortcuts and make ill-advised technical decisions in the initial phases of a project, only to be confronted with the need for costly and labor-intensive workarounds later. This book offers advice on how to avoid technical debt, how to locate its sources, and how to remove it. It focuses on the practical implications of technical debt for the entire software life cycle, with examples and case studies from companies that range from Boeing to Twitter. Technical debt is normal; it is part of most iterative development processes. But if debt is ignored, over time it may become unmanageably complex, requiring developers to spend all of their effort fixing bugs, with no time to add new features--and after all, new features are what customers really value.

Название: Deep Learning-Based Face Analytics
Автор: Nalini K. Ratha, Vishal M. Patel, Rama Chellappa
Издательство: Springer
Год: 2021
Формат: PDF
Страниц: 405
Размер: 15,3 Mb
Язык: English

This book provides an overview of different deep learning-based methods for face recognition and related problems. Specifically, the authors present methods based on autoencoders, restricted Boltzmann machines, and deep convolutional neural networks for face detection, localization, tracking, recognition, etc. The authors also discuss merits and drawbacks of available approaches and identifies promising avenues of research in this rapidly evolving field.