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Indigo AI and Machine Learning for Coders: A Programmer's Guide to Artificial Intelligence | Erin Mills Town Centre
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If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics.
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; and how to serve models over the web and in the cloud with TensorFlow Serving.
If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics.
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; and how to serve models over the web and in the cloud with TensorFlow Serving.
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