AI and Machine Learning for Coders
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You'll understand how to implement the most common scenarios in machine learning, such as computer vision, natural language processing (NLP), and sequence modeling for web, mobile, cloud, and embedded runtimes. Most books on machine learning begin with a daunting amount of advanced math. This guide is built on practical lessons that let you work directly with the code.
You'll learn:
- How to build models with TensorFlow using skills that employers desire
- The basics of machine learning by working with code samples
- How to implement computer vision, including feature detection in images
- How to use NLP to tokenize and sequence words and sentences
- Methods for embedding models in Android and iOS
- How to serve models over the web and in the cloud with TensorFlow Serving
Graderings en resensies
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Laurence Moroney leads AI Advocacy at Google. His goal is to educate the world of software developers in how to build AI systems with Machine Learning. He's a frequent contributor to the TensorFlow YouTube channel at youtube.com/tensorflow, a recognized global keynote speaker and author of more books than he can count, including several best-selling science fiction novels, and a produced screenplay. He's based in Sammamish, Washington where he drinks way too much coffee.
