Publisher: 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.

grid

list

Oracle User Productivity Kit 3.5. Build high-quality training simulations using Oracle UPK 3.5 using this book and

Dirk Manuel

Mastering Redmine. - Second Edition

ANDRIY LESYUK

Hands-On Reactive Programming with Clojure. Create asynchronous, event-based, and concurrent applications - Second Edition

Konrad Szydlo, Leonardo Borges

Building E-commerce Sites with VirtueMart Cookbook. This brilliantly accessible book is the perfect introduction to using all the key features of VirtueMart to set up and install a fully-functioning e-commerce store. From the basics to customization, it's simply indispensable

John Horton

Learn TypeScript 3 by Building Web Applications. Gain a solid understanding of TypeScript, Angular, Vue, React, and NestJS

Sebastien Dubois, Alexis Georges, Basarat Ali Syed

GLSL Essentials. If you're involved in graphics programming, you need to know about shaders, and this is the book to do it. A hands-on guide to the OpenGL Shading Language, it walks you through the absolute basics to advanced techniques

Jacobo Rodriguez

Data Engineering with AWS Cookbook. A recipe-based approach to help you tackle data engineering problems with AWS services

Trâm Ngoc Pham, Gonzalo Herreros González, Viquar Khan, Huda Nofal

Enhancing Deep Learning with Bayesian Inference. Create more powerful, robust deep learning systems with Bayesian deep learning in Python

Matt Benatan, Jochem Gietema, Marian Schneider