Introduction to Machine Learning
1.
Week 1 - Data, Numpy, Matrices, Error/Loss functions and Regression
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Week 2 - Non-Linear Regression, OLS, and Log Loss
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Week 3 - Classification: SVMs, Naive Bayes, KNN and Decision Trees
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Week 4 - Classification & Intro to Unsupervised Learning: Clustering & Dimensional Reduction
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Week 5 - Neural Networks: ANNs, DNNs, and CNNs
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Jupyter Notebook Export Tutorial
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UCSD CSE151A Summer 2025
Week 4 - Classification & Intro to Unsupervised Learning: Clustering & Dimensional Reduction
Week 4 Lecture Material
Lecture Slides
Slides PDF Adv Linear Algebra
Slides PDF PCA & K-Means Intro
Slides PDF SVD & PCA
Slides PDF Implementing Unsupervised Learning Approaches
Notebooks
KNN, PCA, K-means Notebook
PCA & SVD Notebook
Optional Handwriting Notebook
Week 4 Discussion TBA
Week 4 Notebook