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Machine Learning For Dummies - 2nd Edition

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This comprehensive entry-level guide to machine learning introduces readers to a form of artificial intelligence that is crucial for identifying opportunities and solving problems efficiently. Mastering machine learning principles opens up exciting career paths in areas like fraud detection, optimizing search results, real-time advertising, credit scoring, and sophisticated pricing models. Unlike many other resources, the fully updated 2nd Edition does not require years of programming experience, making it accessible to beginners. It covers essential materials to help you start building models for practical tasks and delves into the fascinating math principles behind machine learning, emphasizing that you don't need to be a math expert to create innovative tools. The guide explores the history of AI and machine learning, and provides hands-on experience with Python 3.8 and TensorFlow 2.x, along with downloadable R resources. Readers will learn to build and test their own models using the latest datasets, addressing real-world problems. Whether for academic purposes or to enhance business performance, this friendly guide offers a solid introduction to machine learning, empowering you to confidently engage with this rapidly evolving technology that positively impacts lives globally.

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Machine Learning For Dummies - 2nd Edition, John Paul Mueller, Luca Massaron

Language
Released
2021
Binding
(Paperback),
Book condition
Good
Price
€6.09

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Title
Machine Learning For Dummies - 2nd Edition
Language
English
Released
2021
Format
Paperback
Pages
432
ISBN10
1119724015
ISBN13
9781119724018
Series
Description
This comprehensive entry-level guide to machine learning introduces readers to a form of artificial intelligence that is crucial for identifying opportunities and solving problems efficiently. Mastering machine learning principles opens up exciting career paths in areas like fraud detection, optimizing search results, real-time advertising, credit scoring, and sophisticated pricing models. Unlike many other resources, the fully updated 2nd Edition does not require years of programming experience, making it accessible to beginners. It covers essential materials to help you start building models for practical tasks and delves into the fascinating math principles behind machine learning, emphasizing that you don't need to be a math expert to create innovative tools. The guide explores the history of AI and machine learning, and provides hands-on experience with Python 3.8 and TensorFlow 2.x, along with downloadable R resources. Readers will learn to build and test their own models using the latest datasets, addressing real-world problems. Whether for academic purposes or to enhance business performance, this friendly guide offers a solid introduction to machine learning, empowering you to confidently engage with this rapidly evolving technology that positively impacts lives globally.