Statistical Learning#

Statistical learning combines statistical methods with machine learning techniques to extract insights from data.

Topics#

• Binary Classification
• Regression Analysis
• Best Linear Unbiased Prediction
• Gauss Markov Theorem
• Principal Component Analysis
• Naive Bayes
• Logistic Regression
• Gaussian Mixture Models
• Linear Models
• Wavelet Smoothing
• Bias-Variance Tradeoff
• Multidimensional Splines
• Kernel Density Estimation
• Cross Validation
• Bootstrapping
• Inference Models
• Random Forests
• Latent Variable Modelling
• Boltzmann Machines

Resources#

Books#

• The Elements of Statistical Learning by Trevor Hastie, Robert Tibshirani, Jerome Friedman
• Statistical Learning with Sparsity by Trevor Hastie, Robert Tibshirani, Martin Wainwright
• Introduction to Statistical Learning by Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani

Online Resources#

• MIT: Statistical Learning
• Stanford: Statistical Learning
• CMU: Statistical Learning

Practice Problems#

• Statistical Learning Exercises
• Statistical Learning Problems
• Statistical Learning Challenges