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Python Machine Learning By Example

You're reading from   Python Machine Learning By Example Unlock machine learning best practices with real-world use cases

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Product type Paperback
Published in Jul 2024
Publisher Packt
ISBN-13 9781835085622
Length 518 pages
Edition 4th Edition
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Author (1):
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Yuxi (Hayden) Liu Yuxi (Hayden) Liu
Author Profile Icon Yuxi (Hayden) Liu
Yuxi (Hayden) Liu
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Table of Contents (18) Chapters Close

Preface 1. Getting Started with Machine Learning and Python 2. Building a Movie Recommendation Engine with Naïve Bayes FREE CHAPTER 3. Predicting Online Ad Click-Through with Tree-Based Algorithms 4. Predicting Online Ad Click-Through with Logistic Regression 5. Predicting Stock Prices with Regression Algorithms 6. Predicting Stock Prices with Artificial Neural Networks 7. Mining the 20 Newsgroups Dataset with Text Analysis Techniques 8. Discovering Underlying Topics in the Newsgroups Dataset with Clustering and Topic Modeling 9. Recognizing Faces with Support Vector Machine 10. Machine Learning Best Practices 11. Categorizing Images of Clothing with Convolutional Neural Networks 12. Making Predictions with Sequences Using Recurrent Neural Networks 13. Advancing Language Understanding and Generation with the Transformer Models 14. Building an Image Search Engine Using CLIP: a Multimodal Approach 15. Making Decisions in Complex Environments with Reinforcement Learning 16. Other Books You May Enjoy
17. Index

Building a Movie Recommendation Engine with Naïve Bayes

As promised, in this chapter, we will kick off our supervised learning journey with machine learning classification, and specifically, binary classification. The goal of the chapter is to build a movie recommendation system, which is a good starting point for learning classification from a real-life example—movie streaming service providers are already doing this, and we can do the same.

In this chapter, you will learn the fundamental concepts of classification, including what it does and its various types and applications, with a focus on solving a binary classification problem using a simple, yet powerful, algorithm, Naïve Bayes. Finally, the chapter will demonstrate how to fine-tune a model, which is an important skill that every data science or machine learning practitioner should learn.

We will go into detail on the following topics:

  • Getting started with classification
  • Exploring...
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Python Machine Learning By Example - Fourth Edition
Published in: Jul 2024
Publisher: Packt
ISBN-13: 9781835085622
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