Transparent ML Intro
Overview
Discussion forum
Prerequisites
Linear algebra
Python basics
Numerical programming
Graphics
Loading data
Quiz & summary
Primary
1. Intro ML & transparency
1.1. What is ML?
1.2. ML systems
1.3. ML process
1.4. ML transparency
1.5. K-NN classifier
1.6. Organisation
1.7. Quiz & summary
2. Linear regression
2.1. Simple linear regression
2.2. Multiple linear regression
2.3. Extensions & limitations
2.4. Quiz & summary
3. Logistic regression
3.1. Regress to classify?
3.2. Logistic regression
3.3. Quiz & summary
4. Hypothesis test & software dev
4.1. Hypothesis testing
4.2. Software development
4.3. Quiz & summary
5. Cross validation & bootstrap
5.1. Cross-validation
5.2. Bootstrap
5.3. Quiz & summary
Secondary
6. Feature selection/regularisation
6.1. Feature selection
6.2. Regularisation
6.3. Quiz & summary
7. Trees & ensembles
7.1. Regression trees
7.2. Classification trees
7.3. Ensemble learning
7.4. Quiz & summary
8. GLM & SVM
8.1. Generalised linear models
8.2. Support vector classifiers
8.3. Support vector machines
8.4. Quiz & summary
9. PCA & clustering
9.1. Principal comp. analysis
9.2. Clustering
9.3. Quiz & summary
10. Neural nets & deep learning
10.1. Multilayer neural nets
10.2. Convolutional neural nets
10.3. Recurrent neural nets
10.4. Quiz & summary
Appendices
System transparency
Process transparency
Bibliography
repository
open issue
Index
