Practical Deep Learning for Cloud, Mobile, and Edge

** Featured as a learning resource on the official Keras website **

Whether you're a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach. If your goal is to build something creative, useful, scalable, or just plain cool, this book is for you.

Relying on decades of combined industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use.

List of Chapters Guest-contributed Content The book features chapters from the following industry The book also features content contributed by several industry veterans including François Chollet ( Keras , Google ), Jeremy Howard ( Fast.ai ), Pete Warden ( TensorFlow Mobile ), Anima Anandkumar ( NVIDIA ), Chris Anderson ( 3D Robotics ), Shanqing Cai ( TensorFlow.js ), Daniel Smilkov ( TensorFlow.js ), Cristobal Valenzuela ( ml5.js ), Daniel Shiffman ( ml5.js ), Hart Woolery ( CV 2020 ), Dan Abdinoor ( Fritz ), Chitoku Yato ( NVIDIA Jetson Nano), John Welsh ( NVIDIA Jetson Nano), and Danny Atsmon ( Cognata ).