PHP Persistence: Concepts, Techniques and Practical Solutions with Doctrine by Michael Romer
English | 20 Dec. 2016 | ISBN: 1484225589 | 128 Pages | PDF | 1.1 MB
Take the pain out of dealing with relational databases in an object-oriented programming world. With this short book, you can save time and money by simply coding less while accomplishing more with the Doctrine persistence framework, a leading persistence solution for PHP programmers and web developers. PHP Persistence teaches you about PHP persistence and how to use it effectively for your database-driven applications.
Magento 2 DIY by Viktor Khliupko
English | 7 Jan. 2017 | ISBN: 1484224590 | 196 Pages | PDF | 3.92 MB
Learn how Magento 2, the newest version of the eCommerce platform, works. Aimed at entrepreneurs, marketers, and other experts interested in eCommerce, this book is accessible for anyone who wants to learn how to use Magento with no previous experience.
PHP Arrays: Single, Multi-dimensional, Associative and Object Arrays in PHP 7 by Steve Prettyman
English | 6 Jan. 2017 | ISBN: 1484225554 | 180 Pages | PDF | 1.46 MB
Gain an in-depth understanding of PHP 7 arrays. After a quick overview of PHP 7, each chapter concentrates on single, multi-dimensional, associative, and object arrays. PHP Arrays is a first of its kind book using PHP 7 that demonstrates inserting, appending, updating, and deleting array data.
Beginning Laravel: A beginner's guide to application development with Laravel 5.3 by Sanjib Sinha
English | 8 Jan. 2017 | ISBN: 1484225376 | 208 Pages | PDF | 2.17 MB
Learn about dependency injection, interfaces, service providers, SOLID design, and more with practical and real-world code examples. This book covers everything you need to get started in application development with Laravel 5.3. Beginning Laravel covers features such as method injection, contracts, and authentication.
Machine Learning Using R by Karthik Ramasubramanian
English | 10 Jan. 2017 | ISBN: 1484223330 | 592 Pages | PDF | 11.47 MB
This book is inspired by the Machine Learning Model Building Process Flow, which provides the reader the ability to understand a ML algorithm and apply the entire process of building a ML model from the raw data.