Title : Android Design Patterns and Best Practice Edition : Year : 2016 Authors : Kyle Mew Publisher : Packt Preface Welcome to Android Design Patterns and Best Practice, a comprehensive guide to how to get the most out of your apps with the tried and tested programming philosophy, design patterns. These patterns provide a logical and elegant approach to solving many of the development problems that coders face. These patterns act as a guide creating a clear path from problem to solution, and although applying a design pattern does not guarantee best practice in itself, it will hugely assist the process and make the discovery of design flaws far easier. Design patterns can be implemented on very many platforms and written in as many programming languages. Some code libraries even apply patterns as part of their internal mechanics, and many readers will already be familiar with the Java Observer and Observable...
Title : Web Scraping with Python Edition : Year : 2015 Authors : Richard Lawson Publisher : Packt Preface The Internet contains the most useful set of data ever assembled, which is largely publicly accessible for free. However, this data is not easily reusable. It is embedded within the structure and style of websites and needs to be extracted to be useful. This process of extracting data from web pages is known as web scraping and is becoming increasingly useful as ever more information is available online. What this book covers Chapter 1, Introduction to Web Scraping, introduces web scraping and explains ways to crawl a website. Chapter 2, Scraping the Data, shows you how to extract data from web pages. Chapter 3, Caching Downloads, teaches you how to avoid redownloading by caching results. Chapter 4, Concurrent Downloading, helps you to scrape data faster by downloading in parallel. Chapter 5, Dynamic...
Title : R Deep Learning Essetials Edition : Year : 2016 Authors : Dr. Joshua F. Wiley Publisher : Packt Preface This book is about how to train and use deep learning models or deep neural networks in the R programming language and environment. This book is not intended to provide an in-depth theoretical coverage of deep neural networks, but it will give you enough background to help you understand their basics and use and interpret the results. This book will also show you some of the packages and functions available to train deep neural networks, optimize their hyperparameters to improve the accuracy of your model, and generate predictions or otherwise use the model you built. The book is intended to provide an easy-to-read coverage of the essentials in order to get going with real-life examples and applications. DOWNLOAD (MEGA) | DOWNLOAD (SOLIDFILE) | DOWNLOAD (UPTOBOX) ...
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