Introduction to Machine Learning
1.
Week 1,2 - Data, Numpy, Matrices, Error/Loss functions and Regression
2.
Week 3,4 - Non-Linear Regression, OLS, and Log Loss
3.
Week 5,6 - Classification: SVMs, Naive Bayes, KNN and Decision Trees
4.
Week 7,8 - Classification & Intro to Unsupervised Learning: Clustering & Dimensional Reduction
5.
Week 9,10 - Neural Networks: ANNs, DNNs, and CNNs
6.
Jupyter Notebook Export Tutorial
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UCSD CSE151A Fall 2024
Week 7,8 - Classification & Intro to Unsupervised Learning: Clustering & Dimensional Reduction
Week 7,8 Lecture Material
Lecture Slides
Slides PDF KNNs
Slides PDF SVD & PCA
Slides PDF PCA & K-Means
Slides PDF Adv Linear Algebra
Notebooks
Optional Handwriting Notebook
KNN, PCA, K-means Notebook
PCA & SVD Notebook
Week 7 Discussion
Slides
Notebook
Week 8 Discussion
Slides
Notebook