Machine Learning Algorithms - Second Edition

A detailed reference to build solid foundation of machine learning for building smart applications
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Machine Learning Algorithms - Second Edition

Giuseppe Bonaccorso

A detailed reference to build solid foundation of machine learning for building smart applications
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Book Details

ISBN 139781789347999
Paperback574 pages

Book Description

Machine Learning has gained increasing popularity due to its powerful predictions and very accurate calculated recommendations from the large datasets. However, the true power behind its powerful output is the complex algorithms that involve lots of statistical analysis, churn the large datasets and bring insightful results on the table.

This book will walk you through prominent developments that have taken place around machine learning algorithms, which constitute a very large part of machine learning helping you to strengthen and master the statistical interpretation across supervised, semi-supervised and reinforcement learning areas. When all the main concepts of an algorithm have been exposed, real examples based on the most diffused libraries (like Scikit-Learn, NLTK, Tensorflow and Keras) are presented. You will discover new topics like Semi-supervised Learning, EM Algorithm, Model Capacity, PCA, Independent Component Analysis, Bayesian Regression and Gaussian Mixture. By the end of this book, you will get to grips with each and every machine learning algorithm that are put into production by successful researchers, scientists and can bring the true innovation in your machine learning applications quickly.

Table of Contents

What You Will Learn

  • Understand the feature selection and feature engineering process
  • Assess performance and error trade-offs for Linear Regression
  • Build a data model and understand how it works by using different types of algorithm
  • Learn to tune the parameters of Support Vector Machines
  • Explore the concept of Natural Processing Language and Recommendation Systems

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Table of Contents

Book Details

ISBN 139781789347999
Paperback574 pages
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