Implementing machine learning models - Gómez, Jorge;Hernández, Velssy
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The purpose of this book is to teach the different unsupervised learning models, from their mathematical foundations to the implementation of codes in Python. The idea is to introduce the reader to the supervised learning models, to understand how they operate and to solve problems using these techniques. In the same way, short exercises are solved that can later be replicated in other scenarios. The solved exercises are described step by step, so that the reader can execute them and understand their partial results.

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Produktbeschreibung
The purpose of this book is to teach the different unsupervised learning models, from their mathematical foundations to the implementation of codes in Python. The idea is to introduce the reader to the supervised learning models, to understand how they operate and to solve problems using these techniques. In the same way, short exercises are solved that can later be replicated in other scenarios. The solved exercises are described step by step, so that the reader can execute them and understand their partial results.
Autorenporträt
Jorge Gómez Gómez, Systems Engineer, received a Master's degree in Telematics Engineering at the University of Cauca Colombia in 2010, PhD in Information Technology and Communications at the University of Granada Spain in 2018, Full-time professor of the Systems Engineering program - University of Cordoba, Member IEEE Branch.