Naive Bayes

Summary

A probabilistic classifier based on Bayes' theorem with a (naive) assumption of feature independence — fast, simple, and still competitive for text classification like spam detection.

How to Learn This

1Build a Naive Bayes spam classifier on a small text dataset.
2Learn why the independence assumption is 'naive' yet still works well in practice.
3Compare Multinomial vs. Gaussian Naive Bayes and when each applies.

Support Vector Machines

scikit-learn Basics

More topics in Machine Learning Fundamentals

Supervised vs Unsupervised Learning Linear Regression Logistic Regression Decision Trees Random Forests K-Nearest Neighbors K-Means Clustering Support Vector Machines scikit-learn Basics Train/Test Split Cross-Validation

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