Practical Deep Learning for Cloud, Mobile, and Edge

Meher Anand Kasam is a seasoned software developer who has created apps that are used by tens of millions of people daily. He has released features for a variety of apps, from Square's Point of Sale to the Bing iPhone app, as an iOS developer at Square. He previously worked at Microsoft and Amazon.

Siddha Ganju is a Self-Driving Architect at Nvidia and an AI researcher who was featured in Forbes' 30 Under 30 list. She worked as an AI Advisor at NASA FDL, where she assisted in the development of an automated meteor detection pipeline for NASA's CAMS project, which resulted in the discovery of a comet.

Anirudh Koul is a well-known AI expert, NASA FDL ML Lead, UN/TEDx speaker, author of the Practical Deep Learning book, and a former scientist at Microsoft AI & Research, where he founded Seeing AI, the blind community's most popular technology after the iPhone.

You may have questioned where to start if you're a software engineer interested in deep learning, a seasoned data scientist, or a hobbyist with a simple ambition of creating the next popular AI product. Using a hands-on approach, this step-by-step guide teaches you how to construct practical deep learning apps for the cloud, mobile, browsers, and edge devices. This book is for you if you want to develop something innovative, useful, scalable, or just plain cool.

Anirudh Koul, Siddha Ganju, and Meher Kasam walk you through the process of turning a concept into something that people in the real world can use, drawing on decades of combined industry experience transforming deep learning research into award-winning applications.

What you will learn:

  • Keras, TensorFlow, Core ML, and TensorFlow Lite are used to train, adjust, and deploy computer vision models.
  • Create artificial intelligence for a variety of devices, including the Raspberry Pi, Jetson Nano, and Google Coral.
  • From Silicon Valley's Not Hotdog app to 40+ industry case studies, take a look at some entertaining projects.
  • Simulate an autonomous car in a video game setting and use reinforcement learning to create a tiny replica.
  • Transfer learning can be used to quickly train models.
  • Discover 50+ useful hints for improving model accuracy and performance, as well as troubleshooting and scaling to millions of users.

Some reviews about this book: "Practical leads the title for good reason. For today's ML practices in industry, two priorities loom: staff needs upskilling and models need fine-tuning. This book fast-tracks both."; I am a recent high school graduate, going into my freshman year of college, who is interested in getting into the field of Deep Learning and AI. I found this book to be an incredible resource for accelerating my progress in these fields.”

Authors: Meher Anand Kasam, Siddha Ganju & Anirudh Koul

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