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Publisher's Note: This edition from 2017 is outdated and is not compatible with TensorFlow 2 or any of the most recent updates to Python libraries.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.

Hands-On Full-Stack Web Development with ASP.NET Core. Learn end-to-end web development with leading frontend frameworks, such as Angular, React, and Vue

Tamir Dresher, Amir Zuker, Shay Friedman

Today, full-stack development is the name of the game. Developers who can build complete solutions, including both backend and frontend products, are in great demand in the industry, hence being able to do so a desirable skill. However, embarking on the path to becoming a modern full-stack developer can be overwhelmingly difficult, so the key purpose of this book is to simplify and ease the process.This comprehensive guide will take you through the journey of becoming a full-stack developer in the realm of the web and .NET. It begins by implementing data-oriented RESTful APIs, leveraging ASP.NET Core and Entity Framework. Afterward, it describes the web development field, including its history and future horizons. Then, you’ll build webbased Single-Page Applications (SPAs) by learning about numerous popular technologies, namely TypeScript, Angular, React, and Vue. After that, you’ll learn about additional related concerns involving deployment, hosting, and monitoring by leveraging the cloud; specifically, Azure. By the end of this book, you’ll be able to build, deploy, and monitor cloud-based, data-oriented, RESTful APIs, as well as modern web apps, using the most popular frameworks and technologies.

SAP Business Intelligence Quick Start Guide. Actionable business insights from the SAP BusinessObjects BI platform

Vinay Singh

The SAP BusinessObjects Business Intelligence platform is a powerful reporting and analysis tool. This book is the ideal introduction to the SAP BusinessObjects Business Intelligence platform, introducing you to its data visualization, visual analytics, reporting, and dashboarding capabilities.The book starts with an overview of the BI platform and various data sources for reporting. Then, we move on to looking at data visualization, analysis, reporting, and analytics using BusinessObjects Business Intelligence tools. You will learn about the features associated with reporting, scheduling, and distribution and learn how to deploy the platform. Toward the end, you will learn about the strategies and factors that should be considered during deployment.By the end, you will be confident working with the SAP BusinessObjects Business Intelligence platform to deliver better insights for more effective decision making.

Building Web and Mobile ArcGIS Server Applications with JavaScript. Build exciting custom web and mobile GIS applications with the ArcGIS Server API for JavaScript - Second Edition

Eric Pimpler, Mark Lewin

The ArcGIS API for JavaScript enables you to quickly build web and mobile mapping applications that include sophisticated GIS capabilities, yet are easy and intuitive for the user.Aimed at both new and experienced web developers, this practical guide gives you everything you need to get started with the API. After a brief introduction to HTML/CSS/JavaScript, you'll embed maps in a web page, add the tiled, dynamic, and streaming data layers that your users will interact with, and mark up the map with graphics. You will learn how to quickly incorporate a broad range of useful user interface elements and GIS functionality to your application with minimal effort using prebuilt widgets. As the book progresses, you will discover and use the task framework to query layers with spatial and attribute criteria, search for and identify features on the map, geocode addresses, perform network analysis and routing, and add custom geoprocessing operations. Along the way, we cover exciting new features such as the client-side geometry engine, learn how to integrate content from ArcGIS.com, and use your new skills to build mobile web mapping applications.We conclude with a look at version 4 of the ArcGIS API for JavaScript (which is being developed in parallel with version 3.x) and what it means for you as a developer.

Learn Chart.js. Create interactive visualizations for the Web with Chart.js 2

Helder da Rocha

Chart.js is a free, open-source data visualization library, maintained by an active community of developers in GitHub, where it rates as the second most popular data visualization library. If you want to quickly create responsive Web-based data visualizations for the Web, Chart.js is a great choice.This book guides the reader through dozens of practical examples, complete with code you can run and modify as you wish. It is a practical hands-on introduction to Chart.js. If you have basic knowledge of HTML, CSS and JavaScript you can learn to create beautiful interactive Web Canvas-based visualizations for your data using Chart.js. This book will help you set up Chart.js in a Web page and show how to create each one of the eight Chart.js chart types. You will also learn how to configure most properties that override Chart’s default styles and behaviors. Practical applications of Chart.js are exemplified using real data files obtained from public data portals. You will learn how to load, parse, filter and select the data you wish to display from those files. You will also learn how to create visualizations that reveal patterns in the data. This book is based on Chart.js version 2.7.3 and ES2015 JavaScript.By the end of the book, you will be able to create beautiful, efficient and interactive data visualizations for the Web using Chart.js.

Docker on Windows. From 101 to production with Docker on Windows

Elton Stoneman

Docker is a platform for running server applications in lightweight units called containers. You can run Docker on Windows Server 2016 and Windows 10, and run your existing apps in containers to get significant improvements in efficiency, security, and portability. This book teaches you all you need to know about Docker on Windows, from 101 to deploying highly-available workloads in production. This book takes you on a Docker journey, starting with the key concepts and simple examples of how to run .NET Framework and .NET Core apps in Windows Docker containers. Then it moves on to more complex examples—using Docker to modernize the architecture and development of traditional ASP.NET and SQL Server apps.The examples show you how to break up monoliths into distributed apps and deploy them to a clustered environment in the cloud, using the exact same artifacts you use to run them locally. To help you move confidently to production, it then explains Docker security, and the management and support options. The book finishes with guidance on getting started with Docker in your own projects, together with some real-world case studies for Docker implementations, from small-scale on-premises apps to very large-scale apps running on Azure.

Hands-on Design Patterns with Kotlin. Build scalable applications using traditional, reactive, and concurrent design patterns in Kotlin

Alexey Soshin

Design patterns enable you as a developer to speed up the development process by providing you with proven development paradigms. Reusing design patterns helps prevent complex issues that can cause major problems, improves your code base, promotes code reuse, and makes an architecture more robust.The mission of this book is to ease the adoption of design patterns in Kotlin and provide good practices for programmers. The book begins by showing you the practical aspects of smarter coding in Kotlin, explaining the basic Kotlin syntax and the impact of design patterns. From there, the book provides an in-depth explanation of the classical design patterns of creational, structural, and behavioral families, before heading into functional programming. It then takes you through reactive and concurrent patterns, teaching you about using streams, threads, and coroutines to write better code along the way By the end of the book, you will be able to efficiently address common problems faced while developing applications and be comfortable working on scalable and maintainable projects of any size.

Hands-On Data Science with R. Techniques to perform data manipulation and mining to build smart analytical models using R

Vitor Bianchi Lanzetta, Nataraj Dasgupta, Ricardo Anjoleto Farias

R is the most widely used programming language, and when used in association with data science, this powerful combination will solve the complexities involved with unstructured datasets in the real world. This book covers the entire data science ecosystem for aspiring data scientists, right from zero to a level where you are confident enough to get hands-on with real-world data science problems.The book starts with an introduction to data science and introduces readers to popular R libraries for executing data science routine tasks. This book covers all the important processes in data science such as data gathering, cleaning data, and then uncovering patterns from it. You will explore algorithms such as machine learning algorithms, predictive analytical models, and finally deep learning algorithms. You will learn to run the most powerful visualization packages available in R so as to ensure that you can easily derive insights from your data.Towards the end, you will also learn how to integrate R with Spark and Hadoop and perform large-scale data analytics without much complexity.