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Python Machine Learning By Example

You're reading from   Python Machine Learning By Example Implement machine learning algorithms and techniques to build intelligent systems

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Product type Paperback
Published in Feb 2019
Publisher Packt
ISBN-13 9781789616729
Length 382 pages
Edition 2nd 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 (15) Chapters Close

Preface 1. Section 1: Fundamentals of Machine Learning FREE CHAPTER
2. Getting Started with Machine Learning and Python 3. Section 2: Practical Python Machine Learning By Example
4. Exploring the 20 Newsgroups Dataset with Text Analysis Techniques 5. Mining the 20 Newsgroups Dataset with Clustering and Topic Modeling Algorithms 6. Detecting Spam Email with Naive Bayes 7. Classifying Newsgroup Topics with Support Vector Machines 8. Predicting Online Ad Click-Through with Tree-Based Algorithms 9. Predicting Online Ad Click-Through with Logistic Regression 10. Scaling Up Prediction to Terabyte Click Logs 11. Stock Price Prediction with Regression Algorithms 12. Section 3: Python Machine Learning Best Practices
13. Machine Learning Best Practices 14. Other Books You May Enjoy

Summary

In this chapter, we continued working on the online advertising click-through prediction project. This time, we overcame the categorical feature challenge by means of the one-hot encoding technique. We then resorted to a new classification algorithm logistic regression for its high scalability to large datasets. The in-depth discussion of the logistic regression algorithm stared with the introduction of the logistic function, which led to the mechanics of the algorithm itself. This was followed by how to train a logistic regression using gradient descent. After implementing a logistic regression classifier by hand and testing it on our click-through dataset, we learned how to train the logistic regression model in a more advanced manner, using stochastic gradient descent, and adjusted our algorithm accordingly. We also practiced how to use the SGD-based logistic regression...

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