Machine Learning: A Constraint-Based Approach, 2E by Marco Gori (.PDF)
File Size: 10 MB
Machine Learning: A Constraint-Based Approach, 2nd Edition by Marco Gori, Alessandro Betti, Stefano Melacci
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Overview: Machine Learning: A Constraint-Based Approach, Second Edition provides readers with a refreshing look at the basic models and algorithms of Machine Learning, with an emphasis on current topics of interest that include neural networks and kernel machines. The book presents the information in a truly unified manner that is based on the notion of learning from environmental constraints. It draws a path towards deep integration with Machine Learning that relies on the idea of adopting multivalued logic formalisms, such as in fuzzy systems. Special attention is given to Deep Learning, which nicely fits the constrained-based approach followed in this book. The second edition of this book offers a large number of novel features. Each chapter has been improved by expanding several descriptions, fixing the found errors, and better organizing exercises, thus offering a more accessible presentation of the main concepts. The companion book is paired with Python code that is fully described and discussed in detail, covering problems in vision, language, and others.
Genre: Non-Fiction > Tech & Devices
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