A repo for a study group for StatLearning MOOC on edX We're going to follow along with the mooc course on edx Link to [Mooc on edX] (https://www.edx.org/course/statistical-learning) Alternative link to videos and slides on [dataschool.io](https://www.dataschool.io/15-hours-of-expert-machine-learning-videos/ (h/t Harithaa)
Updated timelines, because life and work got in the way!
Course Starts
First introductory meet-up to discuss time to meet and what we hope to achieve.
- Review & Quiz 1: 1.2 Examples and Framework
- Review & Quiz 2: 2.1 Introduction to Regression Models
- Review & Quiz 3: 2.2 Dimensionality and Structured Models
- Review & Quiz 4: 2.3 Model Selection and Bias-Variance Tradeoff
- Review & Quiz 5: 2.4 Classification
- Review & Quiz 6: 2.R Introduction to R
- Review & Quiz 7: Chapter 2 Quiz
- Review & Quiz 8: 3.1 Simple Linear Regression
- Review & Quiz 9: 3.2 Hypothesis Testing and Confidence Intervals
- Review & Quiz 10: 3.3 Multiple Linear Regression
- Review & Quiz 11: 3.4 Some important questions
- Review & Quiz 12: 3.5 Extensions of the linear model
- Review & Quiz 13: 3.R Linear Regression in R
- Review & Quiz 14: Chapter 3 Quiz
- Review & Quiz 15: 4.1 Introduction to Classification Problems
- Review & Quiz 16: 4.2 Logistic Regression
- Review & Quiz 17: 4.3 Multivariate Logistic Regression
- Review & Quiz 18: 4.4 Logistic Regression - Case-Control Sampling and Multiclass
- Review & Quiz 19: 4.5 Discriminant Analysis
- Review & Quiz 20: 4.6 Gaussian Discriminant Analysis - One Variable
- Review & Quiz 21: 4.7 Gaussian Discriminant Analysis - Many Variables
- Review & Quiz 22: 4.8 Quadratic Discriminant Analysis and Naive Bayes
- Review & Quiz 23: 4.R Classification in R
- Review & Quiz 24: Chapter 4 Quiz
- Review & Quiz 25: 5.1 Cross-validation
- Review & Quiz 26: 5.2 K-fold Cross-Validation
- Review & Quiz 27: 5.3 Cross-Validation: the wrong and right way
- Review & Quiz 28: 5.4 The Bootstrap
- Review & Quiz 29: 5.5 More on the Bootstrap
- Review & Quiz 30: 5.R Resampling in R
- Review & Quiz 31: Chapter 5 Quiz
- Review & Quiz 32: 6.1 Introduction and Best-Subset Selection
- Review & Quiz 33: 6.2 Stepwise Selection
- Review & Quiz 34: 6.3 Backward stepwise selection
- Review & Quiz 35: 6.4 Estimating test error
- Review & Quiz 36: 6.5 Validation and cross-validation
- Review & Quiz 37: 6.6 Shrinkage methods and ridge regression
- Review & Quiz 38: 6.7 The Lasso
- Review & Quiz 39: 6.8 Tuning parameter selection
- Review & Quiz 40: 6.9 Dimension Reduction Methods
- Review & Quiz 41: 6.10 Principal Components Regression and Partial Least Squares
- Review & Quiz 42: 6.R. Model Selection in R
- Review & Quiz 43: Chapter 6 Quiz
- Review & Quiz 44: 7.1 Polynomials and Step Functions
- Review & Quiz 45: 7.2 Piecewise-Polynomials and Splines
- Review & Quiz 46: 7.3 Smoothing Splines
- Review & Quiz 47: 7.4 Generalized Additive Models and Local Regression
- Review & Quiz 48: 7.R Nonlinear Functions in R
- Review & Quiz 49: Chapter 7 Quiz
- Review & Quiz 50: 8.1 Tree-based methods
- Review & Quiz 51: 8.2 More details on Trees
- Review & Quiz 52: 8.3 Classification trees
- Review & Quiz 53: 8.4 Bagging and Random forests
- Review & Quiz 54: 8.5 Boosting
- Review & Quiz 55: 8.R Tree-Based Methods in R
- Review & Quiz 56: Chapter 8 Quiz
- Review & Quiz 57: 9.1 Optimal Separating Hyperplanes
- Review & Quiz 58: 9.2 Support Vector Classifier
- Review & Quiz 59: 9.3 Feature Expansion and the SVM
- Review & Quiz 60: 9.4 Example and Comparison with Logistic Regression
- Review & Quiz 61: 9.R SVMs in R
- Review & Quiz 62: Chapter 9 Quiz
- Review & Quiz 63: 10.1 Principal Components
- Review & Quiz 64: 10.2 Higher Order Principal Components
- Review & Quiz 65: 10.3 k-means Clustering
- Review & Quiz 66: 10.4 Hierarchical Clustering
- Review & Quiz 67: 10.5 Breast Cancer Example
- Review & Quiz 68: 10.R Unsupervised in R
- Review & Quiz 69: Chapter 10 Quiz