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Machine Learning Algorithms

You're reading from   Machine Learning Algorithms A reference guide to popular algorithms for data science and machine learning

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781785889622
Length 360 pages
Edition 1st 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 (16) 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. Linear Regression 5. Logistic Regression 6. Naive Bayes 7. Support Vector Machines 8. Decision Trees and Ensemble Learning 9. Clustering Fundamentals 10. Hierarchical Clustering 11. Introduction to Recommendation Systems 12. Introduction to Natural Language Processing 13. Topic Modeling and Sentiment Analysis in NLP 14. A Brief Introduction to Deep Learning and TensorFlow 15. Creating a Machine Learning Architecture

Further reading

An excellent introduction to artificial intelligence can be found in the first few chapters of Russel S., Norvig P., Artificial Intelligence: A Modern Approach, Pearson. In the second volume, there's also a very extensive discussion on statistical learning in many different contexts. A complete book on deep learning is Goodfellow I., Bengio Y., Courville A., Deep Learning, The MIT Press. If you would like to learn more about how the neocortex works, a simple but stunning introduction is present in Kurzweil R., How to Create a Mind, Duckworth Overlook. A comprehensive introduction to the Python programming language can be found in Lutz M., Learning Python, O'Reilly.

You have been reading a chapter from
Machine Learning Algorithms
Published in: Jul 2017
Publisher: Packt
ISBN-13: 9781785889622
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