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Viser: Practical Deep Learning for Cloud, Mobile, and Edge - Real-World AI and Computer-Vision Projects Using Python, Keras and TensorFlow
Practical Deep Learning for Cloud, Mobile, and Edge Vital Source e-bog
Anirudh Koul, Siddha Ganju og Meher Kasam
(2019)
Practical Deep Learning for Cloud, Mobile, and Edge
Real-World AI and Computer-Vision Projects Using Python, Keras and TensorFlow
Anirudh Koul, Siddha Ganju og Meher Kasam
(2019)
Sprog: Engelsk
om ca. 10 hverdage
Detaljer om varen
- 1. Udgave
- Vital Source searchable e-book (Reflowable pages)
- Udgiver: O'Reilly Media, Inc (Oktober 2019)
- Forfattere: Anirudh Koul, Siddha Ganju og Meher Kasam
- ISBN: 9781492034810
Bookshelf online: 5 år fra købsdato.
Bookshelf appen: ubegrænset dage fra købsdato.
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Detaljer om varen
- 1. Udgave
- Paperback: 624 sider
- Udgiver: O'Reilly Media, Incorporated (November 2019)
- Forfattere: Anirudh Koul, Siddha Ganju og Meher Kasam
- ISBN: 9781492034865
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