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 3,4 - Non-Linear Regression, OLS, and Log Loss
Week 3,4 Lecture Material
Lecture Slides
Slides PDF Polynomial
Slides PDF OLS
Slides PDF Logistic Regression
Slides PDF Data Preprocessing
Slides PDF HPC/SDSC
Notebooks
BCC Data Notebook
Polynomial Regression Notebook
Processing California Housing Notebook
Normality Testing Notebook
Week 3 Discussion
Slides
Notebook
Week 4 Discussion
Slides
Notebook