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Machine Learning Algorithms

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

Product type Paperback

Published in Aug 2018

Publisher Packt

ISBN-13 9781789347999

Length 522 pages

Edition 2nd Edition

Languages

Python

Tools

Scikit-learn

Concepts

Data Science

Author (1):

Giuseppe Bonaccorso

View More author details

Table of Contents (19) Chapters

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

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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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