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.
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
Anirudh Koul is a noted AI expert, NASA ML Lead, UN/TEDx speaker and a former scientist at Microsoft AI & Research, where he founded Seeing AI, the most used technology among the blind community, after the iPhone. With features shipped to a billion users, he brings over a decade of production-oriented applied research experience on petabyte-scale datasets. His work in the AI for Good field, which IEEE has called 'life-changing', has received awards from CES, FCC, MIT, Cannes Lions, American Council of the Blind, showcased at events by UN, World Economic Forum, White House, House of Lords, Netflix, National Geographic, and lauded by world leaders including Justin Trudeau and Theresa May.
Siddha Ganju, an AI researcher who Forbes featured in their 30 under 30 list, is a Self-Driving Architect at Nvidia. As an AI Advisor to NASA FDL, she helped build an automated meteor detection pipeline for the CAMS project at NASA, which ended up discovering a comet. Previously at Deep Vision, she developed deep learning models for edge devices. Her work ranges from Visual Question Answering to GANs to gathering insights from CERN's petabyte-scale data and has been published at top-tier conferences including CVPR and NeurIPS. She has served as a featured jury member in several international tech competitions including CES.
Meher Kasam is a seasoned software developer with apps used by tens of millions of users every day. Currently an iOS developer at Square, and having previously worked at Microsoft and Amazon, he has shipped features for a range of apps from Square's Point of Sale to the Bing iPhone app. At Microsoft, he was the mobile dev lead for the Seeing AI app, which has received many awards from Mobile World Congress, CES, FCC, and the American Council of the Blind, to name a few. A hacker at heart, he won several hackathons and shipped features in widely used products. He serves as a judge of international competitions including Global Mobile Awards and Edison Awards.
