Machine Learning and Deep Learning

Referenced Books

• An Introduction to Statistical Learning
• Understanding Deep Learning

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Table of contents

• Intro to Statistical Machine Learning
• Bias-Variance Tradeoff
• Regression
• Linear Regression
• Sum of Squares
• Ordinary Least Squares
• R-Squared
• Encoding Categorical Variables
• Classification
• Logistic Regression
• Confounding
• Discriminant Analysis
• ROC Curve
• Resampling Methods
• Test Error Estimation / Model Selection
• Regularization
• Decision Tree
• Ensemble Methods
• Random Forest
• Boosted Trees
• Support Vector Machine
• Unsupervised Learning
• Principal Component Analysis
• Clustering
• Shallow Neural Networks
• Deep Neural Networks
• Loss Functions
• Gradient Descent
• Backpropagation
• Regularization in Neural Networks
• Convolutional Neural Networks