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Understanding Machine Learning

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Understanding Machine Learning 1st Edition Solutions Manual

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Edition: 1st Edition


Author: Crazy for study


ISBN: 9781107057135

4.5 Rating

6 Reviews
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Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides a theoretical account of the fundamentals underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics, the book covers a wide array of central topics unaddressed by previous textbooks. These include a discussion of the computational complexity of learning and the concepts of convexity and stability; important algorithmic paradigms including stochastic gradient descent, neural networks, and structured output learning; and emerging theoretical concepts such as the PAC-Bayes approach and compression-based bounds. Designed for advanced undergraduates or beginning graduates, the text makes the fundamentals and algorithms of machine learning accessible to students and non-expert readers in statistics, computer science, mathematics and engineering
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Average Star Rating: 4.5 out of 5 (6 votes)

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    Rated 4 out of 5

    LY DANG THAO KHANH

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    Rated 5 out of 5

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    Rated 4 out of 5

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    Rated 4 out of 5

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    Rated 5 out of 5

    Alireza Alidoosti

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  6. comment avatar

    Rated 5 out of 5

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