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AI and Machine Learning for Coders: A Programmer's Guide to Artificial Intelligence

By: Publication details: Mumbai: Shroff Publishers & Distributors Pvt. Ltd., 2021Description: 365ISBN:
  • 9789385889226
Subject(s): DDC classification:
  • 006.31 MOR
Summary: 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 How to serve models over the web and in the cloud with TensorFlow Serving
List(s) this item appears in: New Arrivals for the Month of September - 2023
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Holdings
Item type Current library Collection Call number Status Date due Barcode Item holds
Book Book Alliance College of Engineering and Design CSE & IT 006.31 MOR (Browse shelf(Opens below)) Checked out 06/09/2024 E12429
Total holds: 0

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
How to serve models over the web and in the cloud with TensorFlow Serving

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