Introduction to Machine Learning
1.
Week 1 - Data, Numpy, Matrices, Error/Loss functions and Regression
2.
Week 2 - Non-Linear Regression, OLS, and Log Loss
3.
Week 3 - Neural Networks: ANNs, DNNs, and CNNs
4.
Week 4 - Classification: SVMs, Naive Bayes, KNN and Decision Trees
5.
Week 5 - Finishing Classification & Intro to Unsupervised Learning: Clustering & Dimensional Reduction
Light
Rust
Coal
Navy
Ayu
UCSD CSE151A Summer Session I 2024
Week 5 - Finishing Classification & Intro to Unsupervised Learning: Clustering & Dimensional Reduction
Deadlines:
Quiz 5 Due 8/4/2024
Homework 4 Due 8/4/2024
Week 5 Lecture Material
Lecture Slides
Slides PDF Decision Trees
Slides PDF KNNs
Slides PDF SVD & PCA
Slides PDF PCA & K-Means
Slides PDF Adv Linear Algebra
Notebooks
Decision Tree Notebook
Optional Handwriting Notebook
KNN, PCA, K-means Notebook
PCA & SVD Notebook
Week 5 Discussion
Discussion Slides
Discussion Notebook