Название: Mathematical Foundations of Data Science Using R
Автор: Matthias Dehmer, Salissou Moutari
Издательство: De Gruyter
Год: 2020
Страниц: 431
Язык: английский
Формат: pdf (true), pdf (conv)
Размер: 30.0 MB, 24.3 MB

In order best exploit the incredible quantities of data being generated in most diverse disciplines data sciences increasingly gain worldwide importance. The book gives the mathematical foundations to handle data properly. It introduces basics and functionalities of the R programming language which has become the indispensable tool for data sciences. Thus it delivers the reader the skills needed to build own tool kits of a modern data scientist.

Название: Hands-on Azure Functions with C#
Автор: Ashirwad Satapathi, Abhishek Mishra
Издательство: Apress
Год: 2021
Формат: PDF
Страниц: 531
Размер: 35,5 Mb
Язык: English

The book starts with an introduction to Azure Functions and demonstrates triggers and bindings with use cases. The process to build an OTP mailer with Queue Storage Trigger and SendGrid output binding is presented, and timer triggers and blob storage binding are covered. Creating custom binding for Azure Functions and building a serverless API using Azure Functions and Azure SQL are discussed. You will know how to build a serverless API using Azure Functions and Azure Cosmos DB, and you will go over enabling application insights and Azure Monitor. Storing function secrets in Azure Key Vault is discussed as well as authentication and authorization using Azure Active Directory. You will learn how to secure your serverless apps using API Management and deploy your Azure Functions using IDEs.

Название: Voice Biometrics: Technology, trust and security
Автор: Carmen García-Mateo, Gerard Chollet
Издательство: The Institution of Engineering and Technology
Год: 2021
Страниц: 300
Язык: английский
Формат: True EPUB
Размер: 10.1 MB

Voice biometrics are being implemented globally in large scale applications such as remote banking, government e-services, transportation and building security access, autonomous vehicles, and healthcare. They have been integrated in numerous apps, often coupled with face biometrics and artificial intelligence methods. Voice biometrics products and solutions must meet three key requirements for the success in their deployment: they must be highly trustable regarding privacy protection; easy to use and always be available. Neural networks, sometimes also called artificial neural networks (ANN), are algorithms for machine learning that consist of a set of units (neurons), which are usually grouped in layers (known as hidden layers) and connected by some weights. This topology allows the model to transform the input data in such a way that it is able to find useful patterns to perform a specific task such as classification or regression. The process of adjusting the values of the connections (weights) is known as training.

Название: Introduction to Statistical and Machine Learning Methods for Data Science
Автор: Carlos Andre Reis Pinheiro, Mike Patetta
Издательство: SAS
Год: 2021
Формат: True PDF, ePUB
Страниц: 170
Размер: 18,5 Mb, 10 Mb
Язык: English

Data science is an exciting, interdisciplinary field that extracts insights from data to solve business problems. This book introduces common data science techniques and methods and shows you how to apply them in real-world case studies. From data preparation and exploration to model assessment and deployment, this book describes every stage of the analytics life cycle, including a comprehensive overview of unsupervised and supervised machine learning techniques. The book guides you through the necessary steps to pick the best techniques and models and then implement those models to successfully address the original business need.

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.

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: 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).