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
Light
Rust
Coal
Navy
Ayu
UCSD CSE151A Fall 2024
Week 1,2 - Data, Numpy, Matrices, Error/Loss functions and Regression
Week 1,2 Lecture Material
Lecture Slides
Slides PDF Syllabus
Slides PDF Introduction
Slides PDF Regression
Week 1 Notebooks
Notebook Tutorial Notebook
CA Housing Notebook
BCC Data Notebook
More coming soon!
Week 1 Discussion
Slides
Notebook
Week 2 Discussion
Slides
Notebook