scikit-learn Basics

Summary

Python's standard ML library — a consistent `fit`/`predict`/`transform` API across dozens of algorithms, and the tool you'll use for most classical ML work.

How to Learn This

1Practice the fit/predict/transform pattern across multiple different estimators.
2Learn to build a `Pipeline` that chains preprocessing and modeling steps.
3Read scikit-learn's algorithm cheat sheet to know what to reach for when.

Naive Bayes

Train/Test Split

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 Naive Bayes Train/Test Split Cross-Validation

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