Practical Deep Learning for Cloud, Mobile and Edge

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

Original Github Repo for Codes: Link

Book PDF: Link