A collection of essential machine learning algorithms implemented from scratch and with libraries. Ideal for students and beginners to understand core ML concepts through hands-on examples.
svm eda knn decisiontree logisticregression outlierdetection onehotencoder kmeansclustering labelencoder linrarregression l1l2regularization nivebayes gradientdecrent batchgd sochasticgd
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Updated
May 23, 2025 - Jupyter Notebook