October 2018
Intermediate to advanced
172 pages
4h 6m
English
Content preview from Machine Learning with scikit-learn Quick Start Guide
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Predicting Categories with Naive Bayes and SVMs
In this chapter, you will learn about two popular classification machine learning algorithms: the Naive Bayes algorithm and the linear support vector machine. The Naive Bayes algorithm is a probabilistic model that predicts classes and categories, while the linear support vector machine uses a linear decision boundary to predict classes and categories.
In this chapter, you will learn about the following topics:
- The theoretical concept behind the Naive Bayes algorithm, explained in mathematical terms
- Implementing the Naive Bayes algorithm by using scikit-learn
- How the linear support vector machine algorithm works under the hood
- Graphically optimizing the hyperparameters of the linear support ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.