This collection features a wide array of simple implementations of machine learning algorithms spanning various methodologies and applications.
naive-bayes linear-regression q-learning self-training gaussian-mixture-models autoencoder logistic-regression t-sne decision-trees polynomial-regression support-vector-machines principal-component-analysis hierarchical-clustering gradient-boosting dbscan-clustering random-forests k-means-clustering k-nearest-neighbors ridge-and-lasso-regression deep-q-networks
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Updated
Jan 10, 2025 - Jupyter Notebook