The DevOps 2.2 Toolkit. Self-Sufficient Docker Clusters

Viktor Farcic

Building on The DevOps 2.0 Toolkit and The DevOps 2.1 Toolkit: Docker Swarm, Viktor Farcic brings his latest exploration of the Docker technology as he records his journey to explore two new programs, self-adaptive and self-healing systems within Docker. The DevOps 2.2 Toolkit: Self-Sufficient Docker Clusters is the latest book in Viktor Farcic’s series that helps you build a full DevOps Toolkit. This book in the series looks at Docker, the tool designed to make it easier in the creation and running of applications using containers. In this latest entry, Viktor combines theory with a hands-on approach to guide you through the process of creating self-adaptive and self-healing systems. Within this book, Viktor will cover a wide-range of emerging topics, including what exactly self-adaptive and self-healing systems are, how to choose a solution for metrics storage and query, the creation of cluster-wide alerts and what a successful self-sufficient system blueprint looks like. Work with Viktor and dive into the creation of self-adaptive and self-healing systems within Docker.

NHibernate 4.x Cookbook. Click here to enter text. - Second Edition

Gunnar Liljas, Alexander Zaytsev, Jason Dentler

NHibernate is a mature, flexible, scalable, and feature-complete open source project for data access. Although it sounds like an easy task to build and maintain database applications, it can be challenging to get beyond the basics and develop applications that meet your needs perfectly. NHibernate allows you to use plain SQL and stored procedures less and keep focus on your application logic instead. Learning the best practices for a NHibernate-based application will help you avoid problems and ensure that your project is a success. The book will take you from the absolute basics of NHibernate through to its most advanced features, showing you how to take full advantage of each concept to quickly create amazing database applications. You will learn several techniques for each of the four core NHibernate tasks—configuration, mapping, session and transaction management, and querying—and which techniques fit best with various types of applications. In short, you will be able to build an application using NHibernate by the end of the book. You will also learn how to best implement enterprise application architecture patterns using NHibernate, leading to clean, easy-to-understand code and increased productivity. In addition to new features, you will learn creative ways to extend the NHibernate core, as well as gaining techniques to work with the NHibernate search, shards, spatial, envers, and validation projects.

Python Machine Learning. Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow - Second Edition

Sebastian Raschka, Vahid Mirjalili

Publisher's Note: This edition from 2017 is outdated and is not compatible with TensorFlow 2 or any of the most recent updates to Python libraries. A new third edition, updated for 2020 and featuring TensorFlow 2 and the latest in scikit-learn, reinforcement learning, and GANs, has now been published.Machine learning is eating the software world, and now deep learning is extending machine learning. Understand and work at the cutting edge of machine learning, neural networks, and deep learning with this second edition of Sebastian Raschka’s bestselling book, Python Machine Learning. Using Python's open source libraries, this book offers the practical knowledge and techniques you need to create and contribute to machine learning, deep learning, and modern data analysis.Fully extended and modernized, Python Machine Learning Second Edition now includes the popular TensorFlow 1.x deep learning library. The scikit-learn code has also been fully updated to v0.18.1 to include improvements and additions to this versatile machine learning library. Sebastian Raschka and Vahid Mirjalili’s unique insight and expertise introduce you to machine learning and deep learning algorithms from scratch, and show you how to apply them to practical industry challenges using realistic and interesting examples. By the end of the book, you’ll be ready to meet the new data analysis opportunities.If you’ve read the first edition of this book, you’ll be delighted to find a balance of classical ideas and modern insights into machine learning. Every chapter has been critically updated, and there are new chapters on key technologies. You’ll be able to learn and work with TensorFlow 1.x more deeply than ever before, and get essential coverage of the Keras neural network library, along with updates to scikit-learn 0.18.1.

Mastering PostGIS. Modern ways to create, analyze, and implement spatial data

Dominik Mikiewicz, Michal Mackiewicz, Tomasz Nycz

PostGIS is open source extension onf PostgreSQL object-relational database system that allows GIS objects to be stored and allows querying for information and location services. The aim of this book is to help you master the functionalities offered by PostGIS- from data creation, analysis and output, to ETL and live edits.The book begins with an overview of the key concepts related to spatial database systems and how it applies to Spatial RMDS. You will learn to load different formats into your Postgres instance, investigate the spatial nature of your raster data, and finally export it using built-in functionalities or 3th party tools for backup or representational purposes. Through the course of this book, you will be presented with many examples on how to interact with the database using JavaScript and Node.js. Sample web-based applications interacting with backend PostGIS will also be presented throughout the book, so you can get comfortable with the modern ways of consuming and modifying your spatial data.

Statistics for Machine Learning. Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R

Pratap Dangeti

Complex statistics in machine learning worry a lot of developers. Knowing statistics helps you build strong machine learning models that are optimized for a given problem statement.This book will teach you all it takes to perform the complex statistical computations that are required for machine learning. You will gain information on the statistics behind supervised learning, unsupervised learning, reinforcement learning, and more. You will see real-world examples that discuss the statistical side of machine learning and familiarize yourself with it. You will come across programs for performing tasks such as modeling, parameter fitting, regression, classification, density collection, working with vectors, matrices, and more.By the end of the book, you will have mastered the statistics required for machine learning and will be able to apply your new skills to any sort of industry problem.

Learning Node.js Development. Learn the fundamentals of Node.js, and deploy and test Node.js applications on the web

Andrew Mead

Learning Node.js Development is a practical, project-based book that provides you with all you need to get started as a Node.js developer. Node is a ubiquitous technology on the modern web, and an essential part of any web developers' toolkit. If you are looking to create real-world Node applications, or you want to switch careers or launch a side project to generate some extra income, then you're in the right place. This book has been written around a single goal—turning you into a professional Node developer capable of developing, testing, and deploying real-world production applications. Learning Node.js Development is built from the ground up around the latest version of Node.js (version 9.x.x). You'll be learning all the cutting-edge features available only in the latest software versions.This book cuts through the mass of information available around Node and delivers the essential skills that you need to become a Node developer. It takes you through creating complete apps and understanding how to build, deploy, and test your own Node apps. It maps out everything in a comprehensive, easy-to-follow package designed to get you up and running quickly.

Ethereum Smart Contract Development. Build blockchain-based decentralized applications using solidity

Mayukh Mukhopadhyay

Ethereum is a public, blockchain-based distributed computing platform featuring smart contract functionality. This book is your one-stop guide to blockchain and Ethereum smart contract development. We start by introducing you to the basics of blockchain. You'll learn about hash functions, Merkle trees, forking, mining, and much more. Then you'll learn about Ethereum and smart contracts, and we'll cover Ethereum virtual machine (EVM) in detail. Next, you'll get acquainted with DApps and DAOs and see how they work. We'll also delve into the mechanisms of advanced smart contracts, taking a practical approach.You'll also learn how to develop your own cryptocurrency from scratch in order to understand the business behind ICO. Further on, you'll get to know the key concepts of the Solidity programming language, enabling you to build decentralized blockchain-based applications. We'll also look at enterprise use cases, where you'll build a decentralized microblogging site. At the end of this book, we discuss blockchain-as-a-service, the dark web marketplace, and various advanced topics so you can get well versed with the blockchain principles and ecosystem.

Spring Boot 2.0 Projects. Build production-grade reactive applications and microservices with Spring Boot

Mohamed Shazin Sadakath

Spring Boot is a lightweight framework that provides a set of tools to create production-grade applications and services. Spring Boot 2.0 Projects is a comprehensive project-based guide for those who are new to Spring, that will get you up to speed with building real-world projects. Complete with clear step-by-step instructions, these easy-to-follow tutorials demonstrate best practices and key insights into building efficient applications with Spring Boot. The book starts off by teaching you how to develop a web application using Spring Boot, followed by giving you an understanding of creating a Spring Boot-based simple blog management system that uses Elasticsearch as the data store. Next, you’ll build a RESTful web services application using Kotlin and the Spring WebFlux framework - a new framework that enables you to create reactive applications in a functional way. Toward the last few chapters, you will build a taxi-hailing API with reactive microservices using Spring Boot, in addition to developing a Twitter clone with the help of a Spring Boot backend. To build on your knowledge further, you’ll also learn how to construct an asynchronous email formatter.By the end of this book, you’ll have a firm foundation in Spring programming and understand how to build powerful, engaging applications in Java using the Spring Boot framework.