Practical Deep Learning for Cloud and Mobile

Practical Deep Learning for Cloud and Mobile - Anirudh Koul

Practical Deep Learning for Cloud and Mobile

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 and mobile 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, CoreML, and TensorFlow Lite and go from zero to a production-quality system quickly.

Develop deep learning applications for the desktop, cloud, smartphones, browser, and Raspberry Pi
Learn by building examples such as Silicon Valley's "Not Hotdog," image search engines, and your own mini-autonomous car
Use transfer learning to train models in minutes
Optimize your apps to run efficiently on different hardware
Discover strategies to scale up from a single user to millions
Sharpen practical skills for data collection, model interoperability, and model debugging using visualizations
Uncover the potential for bias and explore the ethical underpinnings for AI-driven technology
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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 and mobile 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, CoreML, and TensorFlow Lite and go from zero to a production-quality system quickly.

Develop deep learning applications for the desktop, cloud, smartphones, browser, and Raspberry Pi
Learn by building examples such as Silicon Valley's "Not Hotdog," image search engines, and your own mini-autonomous car
Use transfer learning to train models in minutes
Optimize your apps to run efficiently on different hardware
Discover strategies to scale up from a single user to millions
Sharpen practical skills for data collection, model interoperability, and model debugging using visualizations
Uncover the potential for bias and explore the ethical underpinnings for AI-driven technology
Citeste mai mult

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