AI as a Service delves into the convergence of two pivotal technologies: serverless computing and artificial intelligence. Tailored for developers, this book offers a practical, hands-on guide to leveraging these technologies for innovative solutions.

This comprehensive guide uncovers what goes on under the hood and allows you to make the most of the JavaScript language and the Node runtime, making it a reliable reference for newer and more experienced developers alike

Explore every relevant aspect of data analytics—from data engineering to analysis, business intelligence, DevOps, and MLOps —as you discover how to integrate machine learning predictions with analytics engines and visualisation tools.

Become a Node.js expert with Node.js Design Patterns. This comprehensive guide takes you from the basics to advanced techniques, offering tested patterns and strategies for designing and implementing production-grade Node.js applications.

Unlock the potential of the Rust programming language for building Lambda functions that excel in efficiency, cost-effectiveness, and sustainability. This practical e-book covers everything you need to know to write, test, and deploy Lambda functions in Rust.

Updated for OpenCV 5, this book covers the latest on depth cameras, 3D navigation, deep neural networks, and Cloud computing, helping you solve real-world computer vision problems with practical code

Step into the world of neural networks with R Deep Learning Essentials. This step-by-step guide helps you build deep learning models using TensorFlow, Keras, and MXNet, all within the R ecosystem, empowering you to create powerful AI solutions.

Master the art of building fast, efficient, and scalable client-server solutions with the latest versions of Node.js. Node Cookbook provides you with essential debugging tips, an understanding of streams in Node.js, and the implementation of various web protocols.

Updated for OpenCV 4 and Python 3, this book covers the latest on depth cameras, 3D tracking, augmented reality, and deep neural networks, helping you solve real-world computer vision problems with practical code.

This book provides a comprehensive Learning Path to mastering deep learning with R, starting from building neural networks from scratch to tackling advanced concepts like GANs, transfer learning, and large-scale cloud deployment.