Practical Deep Learning for Cloud, Mobile, and Edge

This is the official code repository for the O'Reilly Publication, Practical Deep Learning for Cloud, Mobile, and Edge by Anirudh Koul, Siddha Ganju and Meher Kasam. ** Featured as a learning resource on the official Keras website **

[Online on Safari] | [Buy on Amazon] | [Online on Google Books] | [Book Website] | [Presentation on Slideshare]

Book Description

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 do I begin? This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browser, and edge devices using a hands-on approach.

Relying on years of 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.

• Train, tune, and deploy computer vision models with Keras, TensorFlow, Core ML, and TensorFlow Lite
• Develop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google Coral
• Explore fun projects, from Silicon Valley’s "Not Hotdog" app to 40+ industry case studies
• Simulate an autonomous car in a video game environment and build a miniature version with reinforcement learning.
• Use transfer learning to train models in minutes
• Discover 50+ practical tips for maximizing model accuracy and speed, debugging, and scaling to millions of users