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.

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GNS3 Network Simulation Guide. From installation through to creating large scale simulations, this is the complete guide to GNS3 that will give you the know-how needed for Cisco certification. For networking professionals, it's a career-advancing tutorial

GNS3, Christopher J Welsh (USD)

Drupal 7 Media. Integrate, implement, and extend rich media resources such as images, videos, and audio on your Drupal 7 website with this book and ebook - Third Edition

Liran Tal

Technical Program Manager's Handbook. Empowering managers to efficiently manage technical projects and build a successful career path

Joshua Alan Teter, Ben Tobin

Unreal Engine: Game Development from A to Z. Your complete companion to game development in Unreal Engine 4

Nitish Misra, John P. Doran, Joanna Lee

Hadoop Beginner's Guide. Get your mountain of data under control with Hadoop. This guide requires no prior knowledge of the software or cloud services – just a willingness to learn the basics from this practical step-by-step tutorial

Gerald Turkington, Kevin A. McGrail

Mastering Adobe Photoshop Elements 2022. Boost your image-editing skills using the latest Adobe Photoshop Elements tools and techniques - Fourth Edition

Robin Nichols

Scalable Data Architecture with Java. Build efficient enterprise-grade data architecting solutions using Java

Sinchan Banerjee

Applied Machine Learning Explainability Techniques. Make ML models explainable and trustworthy for practical applications using LIME, SHAP, and more

Aditya Bhattacharya