Видавець: Packt Publishing
Founded in 2004 in Birmingham, UK, Packt's mission is to help the world put software to work in new ways, through the delivery of effective learning and information services to IT professionals. Working towards that vision, we have published over 6,500 books and videos so far, providing IT professionals with the actionable knowledge they need to get the job done - whether that's specific learning on an emerging technology or optimizing key skills in more established tools. As part of our mission, we have also awarded over $1,000,000 through our Open Source Project Royalty scheme, helping numerous projects become household names along the way.
937
Eлектронна книга

Ensemble Machine Learning Cookbook. Over 35 practical recipes to explore ensemble machine learning techniques using Python

Dipayan Sarkar, Vijayalakshmi Natarajan

Ensemble modeling is an approach used to improve the performance of machine learning models. It combines two or more similar or dissimilar machine learning algorithms to deliver superior intellectual powers. This book will help you to implement popular machine learning algorithms to cover different paradigms of ensemble machine learning such as boosting, bagging, and stacking.The Ensemble Machine Learning Cookbook will start by getting you acquainted with the basics of ensemble techniques and exploratory data analysis. You'll then learn to implement tasks related to statistical and machine learning algorithms to understand the ensemble of multiple heterogeneous algorithms. It will also ensure that you don't miss out on key topics, such as like resampling methods. As you progress, you’ll get a better understanding of bagging, boosting, stacking, and working with the Random Forest algorithm using real-world examples. The book will highlight how these ensemble methods use multiple models to improve machine learning results, as compared to a single model. In the concluding chapters, you'll delve into advanced ensemble models using neural networks, natural language processing, and more. You’ll also be able to implement models such as fraud detection, text categorization, and sentiment analysis.By the end of this book, you'll be able to harness ensemble techniques and the working mechanisms of machine learning algorithms to build intelligent models using individual recipes.

938
Eлектронна книга

Fixing Bad UX Designs. Master proven approaches, tools, and techniques to make your user experience great again

Lisandra Maioli

Have your web applications been experiencing more hits and less conversions? Are bad designs consuming your time and money?This book is the answer to these problems. With intuitive case studies, you’ll learn to simplify, fix, and enhance some common, real-world application designs. You’ll look at the common issues of simplicity, navigation, appearance, maintenance, and many more.The challenge that most UX designers face is to ensure that the UX is user-friendly. In this book, we address this with individual case studies starting with some common UX applications and then move on to complex applications. Each case study will help you understand the issues faced by a bad UX and teach you to break it down and fix these problems.As we progress, you’ll learn about the information architecture, usability testing, iteration, UX refactoring, and many other related features with the help of various case studies. You’ll also learn some interesting UX design tools with the projects covered in the book.By the end of the book, you’ll be armed with the knowledge to fix bad UX designs and to ensure great customer satisfaction for your applications.

939
Eлектронна книга

Game Development Patterns and Best Practices. Better games, less hassle

John P. Doran, Matt Casanova

You’ve learned how to program, and you’ve probably created some simple games at some point, but now you want to build larger projects and find out how to resolve your problems. So instead of a coder, you might now want to think like a game developer or software engineer. To organize your code well, you need certain tools to do so, and that’s what this book is all about. You will learn techniques to code quickly and correctly, while ensuring your code is modular and easily understandable.To begin, we will start with the core game programming patterns, but not the usual way. We will take the use case strategy with this book. We will take an AAA standard game and show you the hurdles at multiple stages of development. Similarly, various use cases are used to showcase other patterns such as the adapter pattern, prototype pattern, flyweight pattern, and observer pattern. Lastly, we’ll go over some tips and tricks on how to refactor your code to remove common code smells and make it easier for others to work with you. By the end of the book you will be proficient in using the most popular and frequently used patterns with the best practices.

940
Eлектронна книга

The Agile Developer's Handbook. Get more value from your software development: get the best out of the Agile methodology

Paul Flewelling

This book will help you overcome the common challenges you’ll face when transforming your working practices from waterfall to Agile. Each chapter builds on the last, starting with easy-to-grasp ways to get going with Agile. Next you’ll see how to choose the right Agile framework for your organization. Moving on, you’ll implement systematic product delivery and measure and report progress with visualization. Then you’ll learn how to create high performing teams, develop people in Agile, manage in Agile, and perform distributed Agile and collaborative governance.At the end of the book, you’ll discover how Agile will help your company progressively deliver software to customers, increase customer satisfaction, and improve the level of efficiency in software development teams.

941
Eлектронна книга

R Data Visualization Recipes. A cookbook with 65+ data visualization recipes for smarter decision-making

Vitor Bianchi Lanzetta

R is an open source language for data analysis and graphics that allows users to load various packages for effective and better data interpretation. Its popularity has soared in recent years because of its powerful capabilities when it comes to turning different kinds of data into intuitive visualization solutions.This book is an update to our earlier R data visualization cookbook with 100 percent fresh content and covering all the cutting edge R data visualization tools. This book is packed with practical recipes, designed to provide you with all the guidance needed to get to grips with data visualization using R. It starts off with the basics of ggplot2, ggvis, and plotly visualization packages, along with an introduction to creating maps and customizing them, before progressively taking you through various ggplot2 extensions, such as ggforce, ggrepel, and gganimate. Using real-world datasets, you will analyze and visualize your data as histograms, bar graphs, and scatterplots, and customize your plots with various themes and coloring options. The book also covers advanced visualization aspects such as creating interactive dashboards using ShinyBy the end of the book, you will be equipped with key techniques to create impressive data visualizations with professional efficiency and precision.

942
Eлектронна книга

Mastering Microsoft Dynamics CRM 2016. An advanced guide for effective Dynamics CRM customization and development

Deepesh Somani

Microsoft Dynamics CRM is the most trusted name in enterprise-level customer relationship management. The latest version of Dynamics CRM 2016 comes with some exciting extra features guaranteed to make your life easier with Dynamics CRM. This book provides a comprehensive coverage of Dynamics CRM 2016 and helps you make your tasks much simpler while elevating you to the level of an expert.The book starts with a brief overview of the functional features and then introduces the latest features of Dynamics CRM 2016. You will learn to create Word and Excel templates, using CRM data that will enable you to provide customized data analysis for your organization. You will understand how to utilize Dynamics CRM as an XRM Framework, gain a deep understanding about client-side scripting in Dynamics CRM, and learn creating client-side applications using JavaScript and Web API. We then introduce visual control frameworks for Dynamics CRM 2016 mobile and tablet applications. Business Process Flows, Business Rules, and their enhancements are introduced. By the end of this book, you will have mastered utilizing Dynamics CRM 2016 features through real-world scenarios.

943
Eлектронна книга

Windows Server 2016 Administration Cookbook. Core infrastructure, IIS, Remote Desktop Services, Monitoring, and Group Policy

Jordan Krause

Windows Server 2016 is an operating system designed to run on servers. It supports enterprise-level data storage, communications, management, and applications. This book contains specially selected, detailed help on core, essential administrative tasks of Windows Server 2016.This book starts by helping you to navigate the interface of Windows Server 2016, and quickly shifts gears to implementing roles that are necessarily in any Microsoft-centric datacenter.This book will also help you leverage the web services platform built into Windows Server 2016, available to anyone who runs this latest and greatest Server operating system. Further, you will also learn to compose optimal Group Policies and monitor system performance and IP address management.This book will be a handy quick-reference guide for any Windows Server administrator, providing easy to read, step-by-step instructions for many common administrative tasks that will be part of any Server Administrator’s job description as they administer their Windows Server 2016 powered servers.The material in the book has been selected from the content of Packt's Windows Server 2016 Cookbook by Jordan Krause to provide a specific focus on key Windows Server administration tasks.

944
Eлектронна книга

Machine Learning Algorithms. A reference guide to popular algorithms for data science and machine learning

Giuseppe Bonaccorso

In this book, you will learn all the important machine learning algorithms that are commonly used in the field of data science. These algorithms can be used for supervised as well as unsupervised learning, reinforcement learning, and semi-supervised learning. The algorithms that are covered in this book are linear regression, logistic regression, SVM, naïve Bayes, k-means, random forest, TensorFlow and feature engineering.In this book, you will how to use these algorithms to resolve your problems, and how they work. This book will also introduce you to natural language processing and recommendation systems, which help you to run multiple algorithms simultaneously.On completion of the book, you will know how to pick the right machine learning algorithm for clustering, classification, or regression for your problem