Название: DevOps: Step-by-Step Guide of Development and IT Operations. Advocate Better Communication and Collaboration Between Business Units
Автор: Yughi Chan
Издательство: Amazon.com Services LLC
Год: 2020
Страниц: 248
Язык: английский
Формат: pdf (conv), rtf, epub
Размер: 10.1 MB

Will it be strange when the application development team and operation team start working together? You will be surprised. Won’t you? Definitely they have been isolated for a very long time. But now the process introduced by DevOps has made the development team and operation team work together for more production. In past several years, DevOps has proved itself one of the hottest IT trends. Plenty of success stories have been introduced and results are more stunning due to DevOps effectiveness with software developments for any size of organization, IT levels and any industry around the globe.

Название: Grokking Deep Reinforcement Learning (MEAP Version 11)
Автор: Miguel Morales
Издательство: Manning Publications
Год: 2020
Формат: true pdf/epub
Страниц: 399
Размер: 41.1 Mb
Язык: English

Grokking Deep Reinforcement Learning is a beautifully balanced approach to teaching, offering numerous large and small examples, annotated diagrams and code, engaging exercises, and skillfully crafted writing. You'll explore, discover, and learn as you lock in the ins and outs of reinforcement learning, neural networks, and AI agents. You will go from small grid world environments and some of the foundational algorithms to some of the most challenging environments out there today and cutting-edge techniques to solve these environments.

Название: Machine Learning with R, tidyverse, and mlr (MEAP)
Автор: Hefin I. Rhys
Издательство: Manning Publications
Год: 2019
Формат: true pdf/epub
Страниц: 513
Размер: 36.6 Mb
Язык: English

Machine Learning with R, tidyverse, and mlr teaches you how to gain valuable insights from your data using the powerful R programming language. In his engaging and informal style, author and R expert Hefin Ioan Rhys lays a firm foundation of ML basics and introduces you to the tidyverse, a powerful set of R tools designed specifically for practical data science. Armed with the fundamentals, you’ll delve deeper into commonly used machine learning techniques including classification, prediction, reduction, and clustering algorithms, applying each to real data to make predictions on fun and interesting problems.
Using the tidyverse packages, you’ll transform, clean, and plot your data, onboarding data science best practices as you go.

Название: Microservices: A Practical Guide: Principles, Concepts, and Recipes, Second Edition
Автор: Eberhard Wolff
Издательство: CreateSpace Independent Publishing Platform
Год: 2019
Формат: true pdf/epub
Страниц: 319
Размер: 17 Mb
Язык: English

Microservices have many advantages: Efficiently implementing more features, bringing software into production faster, robustness and easy scalability are among them. But implementing a microservices architecture and selecting the necessary technologies are difficult challenges.This book shows microservices recipes that architects can customize and combine into a microservices menu. In this way, the implementation of microservices can be individually adapted to the requirements of the project.Eberhard Wolff introduces microservices, self-contained systems, micro- and macro-architecture and the migration to microservices. The second part shows the microservices recipes: Basic technologies such as Docker or PaaS, frontend integration with links, jаvascript or ESI (Edge Side Includes).

Название: Learn Quantum Computing with Python and Q#: A hands-on approach (MEAP)
Автор: Sarah C. Kaiser and Christopher E. Granade
Издательство: Manning Publications
Год: 2020
Формат: true pdf/epub
Страниц: 266
Размер: 17 Mb
Язык: English

Learn Quantum Computing with Python and Q# demystifies quantum computing. Using Microsoft’s Quantum Development Kit to abstract away the mathematical complexities, this book builds your understanding of quantum computers by actively developing for them. You’ll start by learning QC fundamentals by creating your own quantum simulator in Python. Soon you’ll move on to using the QDK and the new Q# language for writing and running algorithms very different to those found in classical computing. When you’re finished you’ll be able to apply quantum programming techniques to applications like quantum key distribution, and tackle real-world examples such as chemistry simulations and searching unsorted databases.

Название: Arduino: Simple and Effective Strategies to Arduino Programming
Автор: Ethan Thorpe
Издательство: Independently published
Год: 2019
Формат: epub/mobi/pdf(conv.)
Страниц: 228
Размер: 11 Mb
Язык: English

This book is for electronics and embedded system enthusiasts. With the help of our smart little superhero ARDUINO, you’ll be able to reproduce many things in your home that you only see in the movies.
We will start from the absolute basics. Hence no prior programming knowledge is required to understand and perform the projects in this book. This book is a complete step by step guide to get acquainted with the Arduino platform and learn how to program the Arduino boards. We will also teach you the C programming language used to program the microcontrollers and basic concepts of the programming.

Название: Blockchain Cybersecurity, Trust and Privacy (Advances in Information Security)
Автор: Kim-Kwang Raymond Choo (Editor), Ali Dehghantanha (Editor), Reza M. Parizi (Editor)
Издательство: Springer
Год: 2020
Формат: true pdf/epub
Страниц: 290
Размер: 40.8 Mb
Язык: English

This book provides the reader with the most up-to-date knowledge of blockchain in mainstream areas of security, trust, and privacy in the decentralized domain, which is timely and essential (this is due to the fact that the distributed and P2P applications is increasing day-by-day, and the attackers adopt new mechanisms to threaten the security and privacy of the users in those environments). This book also provides the technical information regarding blockchain-oriented software, applications, and tools required for the researcher and developer experts in both computing and software engineering to provide solutions and automated systems against current security, trust and privacy issues in the cyberspace.

Название: Succeeding with AI How to get the results you want (MEAP)
Автор: Veljko Krunic
Издательство:
Год: 2019
Формат: true pdf/epiub/azw3
Страниц: 272
Размер: 10 Mb
Язык: English

In Succeeding with AI, author and AI consultant Veljko Krunic reveals secrets for succeeding in AI that he developed with Fortune 500 companies, early-stage startups, and other businesses across multiple industries. Veljko first lays out a framework for determining the right questions to answer for your business. Then, he teaches you a repeatable process for properly organizing an AI project to maximize the value of limited sources, such as the time of your data scientists. You’ll learn to establish metrics that let you judge the effectiveness of your machine learning against business needs and how to assess whether your AI project is on the right track early on in its lifecycle.

Название: Deep Reinforcement Learning in Action (MEAP)
Автор: Alexander Zai and Brandon Brown
Издательство: Manning Publications
Год: 2020
Формат: true pdf/epub
Страниц: 351
Размер: 12.2 Mb
Язык: English

Deep Reinforcement Learning in Action teaches you how to program agents that learn and improve based on direct feedback from their environment. You’ll build networks with the popular PyTorch deep learning framework to explore reinforcement learning algorithms ranging from Deep Q-Networks to Policy Gradients methods to Evolutionary Algorithms. As you go, you’ll apply what you know to hands-on projects like controlling simulated robots, automating stock market trades, and even building a bot to play Go.

Название: Machine Learning for Subsurface Characterization
Автор: Siddharth Misra, Hao Li
Издательство: Gulf Professional Publishing
Год: 2019
Страниц: 442
Язык: английский
Формат: pdf (true)
Размер: 86.1 MB

Machine Learning for Subsurface Characterization develops and applies neural networks, random forests, deep learning, unsupervised learning, Bayesian frameworks, and clustering methods for subsurface characterization. Machine Learning (ML) focusses on developing computational methods/algorithms that learn to recognize patterns and quantify functional relationships by processing large data sets, also referred to as the 'big data.' Deep learning (DL) is a subset of machine learning that processes 'big data' to construct numerous layers of abstraction to accomplish the learning task.