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 3 - Neural Networks: ANNs, DNNs, and CNNs
Deadlines:
Quiz 3 Due 7/22/2024
Homework 2 Due 7/22/2024
Week 3 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 3 Discussion
Discussion Slides
Discussion Notebook