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Overview
Machine Learning
Basic Concepts
Data
Model
Model Overview
Linear and Logistic Regression
Bayes' Theorem and Naive Bayes
k-Means Clustering
Principal Component Analysis (PCA)
Support Vector Machines
Tree-based Methods
Ensemble Learning
Training
Evaluation
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Docs
Machine Learning
Evaluation
Evaluation
Key topics:
Metrics: precision/recall, ROC-AUC, PR-AUC, calibration.
Validation: K-fold, time-series CV, leakage checks.
Offline vs. online evaluation and experiment design.
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Training