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]
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