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 - Classification: SVMs, Naive Bayes, KNN and Decision Trees
4.
Week 4 - Classification & Intro to Unsupervised Learning: Clustering & Dimensional Reduction
5.
Week 5 - Neural Networks: ANNs, DNNs, and CNNs
6.
Jupyter Notebook Export Tutorial
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UCSD CSE151A Summer 2025
Week 5 - Neural Networks: ANNs, DNNs, and CNNs
Week 5 Lecture Material
Lecture Slides
Slides PDF Perceptrons
Slides PDF Adv. Neural Networks
Slides PDF Gradient Descent
Slides PDF Convolutions
Notebooks
BCC Data Notebook
Perceptron Notebook
ANN Notebook
Convolution Notebook
Gradient Descent Notebook
Week 5 Discussion
Notebook