README
CS229
all the ppts, notes and homework for CS229 taught by Andrew Ng
- Last pushed 6y agoCommit history
- mathematics_foundation
- python_tutorial
- BiasVarianceAnalysis.pdf
- boosting.pdf
- critiques-ml-aut19.pdf
- cs229-notes-backprop.pdf
- cs229-notes-deep_learning.pdf
- cs229-notes-dt.pdf
- cs229-notes6.pdf
- decision_tree_demo.ipynb
- deep_learning.pdf
- EM.pdf
- evaluation_metrics.pdf
- Factor analysis.pdf
- Generative Model.pdf
- ICA.pdf
- K-means.pdf
- LearningTheory.pdf
- Linear Model.pdf
- loss-functions.pdf
- midterm-review.pdf
- Mixtures of Gaussians.pdf
- ML-advice.pdf
- PCA.pdf
- README.md
- Regularization and model selection.pdf
- reinforce_learning.pdf
- representer-function.pdf
- stanford-cs229
- SVM.pdf
- weak_supervision_notes.pdf
- weak_supervision_slides.pdf