Confusion Matrix Threshold Lab
Interactive threshold tuning lab for precision/recall tradeoffs, confusion-matrix intuition, and classifier decision policy design.
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Interactive threshold tuning lab for precision/recall tradeoffs, confusion-matrix intuition, and classifier decision policy design.
Watch matrices transform vectors, discover the directions that do not turn, and connect eigenvectors to PCA and machine learning.
Interactive optimization lab to tune learning rate, observe convergence behavior, and build intuition for gradient-descent stability.
Learn every Naive Bayes calculation, experiment with a live spam filter, and implement the complete classifier from scratch and with scikit-learn in Google Colab.