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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Building Mobile Applications Using Kendo UI Mobile and ASP.NET Web API. Confident of your web application skills but not yet au fait with mobile development? Well this book helps you use the Kendo UI for a painless introduction. Practical tasks and clear instructions make learning a breeze

Ragini Kumbhat Bhandari, Nishanth Nair, Ragini Bhandari

Effective Concurrency in Go. Develop, analyze, and troubleshoot high performance concurrent applications with ease

Burak Serdar

Hands-On Data Preprocessing in Python. Learn how to effectively prepare data for successful data analytics

Roy Jafari

AI Crash Course. A fun and hands-on introduction to machine learning, reinforcement learning, deep learning, and artificial intelligence with Python

Hadelin de Ponteves

Microsoft SQL Server 2012 with Hadoop. Getting SQL Server talking to Hadoop is a smooth process when you follow this tutorial. Learn all the tools and techniques you need integrate the data and then extract powerful business insights from the merged result

Debarchan Sarkar

Engineering Data Mesh in Azure Cloud. Implement data mesh using Microsoft Azure's Cloud Adoption Framework

Aniruddha Deswandikar

Microsoft Hyper-V PowerShell Automation. Manage, automate, and streamline your Hyper-V environment effectively with advanced PowerShell cmdlets

Vinith Menon

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

Aditya Bhattacharya