Phase 02: 机器学习基础

本阶段包含 18 课时。

原始课程来源：AI Engineering from Scratch (MIT License)

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• What Is Machine Learning
• Linear Regression
• Logistic Regression
• Decision Trees and Random Forests
• Support Vector Machines
• K-Nearest Neighbors and Distances
• Unsupervised Learning
• Feature Engineering & Selection
• Model Evaluation
• Bias-Variance Tradeoff
• Ensemble Methods
• Hyperparameter Tuning
• ML Pipelines
• Naive Bayes
• Time Series Fundamentals
• Anomaly Detection
• Handling Imbalanced Data
• Feature Selection