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 - Neural Networks: ANNs, DNNs, and CNNs
4.
Week 4 - Classification: SVMs, Naive Bayes, KNN and Decision Trees
5.
Week 5 - Finishing Classification & Intro to Unsupervised Learning: Clustering & Dimensional Reduction
Light
Rust
Coal
Navy
Ayu
UCSD CSE151A Summer Session I 2024
Week 2 - Non-Linear Regression, OLS, and Log Loss
Deadlines:
Quiz 2 Due 7/14/2024
Homework 1 Due 7/14/2024
Week 2 Lecture Material
Lecture Slides
Slides PDF Polynomial
Slides PDF OLS
Slides PDF Logistic Regression
Slides PDF Data Preprocessing
Slides PDF HPC/SDSC
Slides PDF Perceptrons
Notebooks
BCC Data Notebook
Polynomial Regression Notebook
Processing California Housing Notebook
Normality Testing Notebook
Perceptron Notebook
Week 2 Discussion
Discussion Slides
Discussion Notebook