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Machine Learning Algorithms

You're reading from   Machine Learning Algorithms Popular algorithms for data science and machine learning

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Product type Paperback
Published in Aug 2018
Publisher Packt
ISBN-13 9781789347999
Length 522 pages
Edition 2nd Edition
Languages
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Author (1):
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Giuseppe Bonaccorso Giuseppe Bonaccorso
Author Profile Icon Giuseppe Bonaccorso
Giuseppe Bonaccorso
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Table of Contents (19) Chapters Close

Preface 1. A Gentle Introduction to Machine Learning FREE CHAPTER 2. Important Elements in Machine Learning 3. Feature Selection and Feature Engineering 4. Regression Algorithms 5. Linear Classification Algorithms 6. Naive Bayes and Discriminant Analysis 7. Support Vector Machines 8. Decision Trees and Ensemble Learning 9. Clustering Fundamentals 10. Advanced Clustering 11. Hierarchical Clustering 12. Introducing Recommendation Systems 13. Introducing Natural Language Processing 14. Topic Modeling and Sentiment Analysis in NLP 15. Introducing Neural Networks 16. Advanced Deep Learning Models 17. Creating a Machine Learning Architecture 18. Other Books You May Enjoy

Who this book is for

This book is for machine learning engineers, data engineers, and data scientists who want to build a strong foundation in the field of predictive analytics and machine learning. Familiarity with Python would be an added advantage and will enable you to get the most out of this book.

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