Machine Learning Notes

Notebook 00 Python Basics

• NumPy
  • NumPy array manipulation
  • NumPy calculation (linalg, matmul, etc.)
• Matplotlib
  • Simple plot
  • Plot styles
  • Subplots
  • 3D plot

Notebook 01 Regression

• Linear Model
• LASSO and Ridge

Notebook 02 Feature

• Feature exploration and visualization

Notebook 03 Bias and Variance

• Bias and variance decomposition

Notebook 04 Maximum Likelihood Estimation

• MLE on Normal Distribution
• Compare biased and unbiased estimators

Notebook 05 Optimization Methods

• Gradient decent
• Newton's method

Notebook 06 Classification

• Perceptron
• Logistic Regression
• Softmax Regression

Notebook 07 Nonparametric Modeling

• kNN
• Decision Tree
• The curse of dimensionality

Notebook 08 Ensemble Learning

• Bootstrap Aggregation (Bagging)
• Random Forest Regression
• Adaptive Boosting (AdaBoost)
• Gradient Boost

Notebook 09 Neural Learning

Notebook 10 Unsupervised Learning

• PCA
• k-Means

Notebook 11 PyTorch