Machine Learning Foundations
The statistical learning theory underneath everything else here.
14 topics · 2 curated works
Topics
- 01Supervised Learning
- 02Unsupervised Learning
- 03Bias-Variance Tradeoff
- 04Overfitting & Regularisation
- 05Cross-Validation
- 06Feature Engineering
- 07Linear & Logistic Regression
- 08Decision Trees & Random Forests
- 09Gradient Boosting
- 10Support Vector Machines
- 11Clustering Methods
- 12Dimensionality Reduction
- 13Statistical Learning Theory
- 14Evaluation Metrics
Curated reading
2Start here
No prior grounding assumed.
Go deeper
Primary sources and full treatments.
- BookThe Elements of Statistical LearningTrevor Hastie, Robert Tibshirani & Jerome Friedman, 2001
The reference account of supervised and unsupervised learning as statistics, written before the field renamed itself.
Also covered elsewhere
This subject genuinely sits in more than one domain. These fields approach the same ground with different methods.