1. Introduction to Machine Learning
  2. 1. Week 1 - Data, Numpy, Matrices, Error/Loss functions and Regression
  3. 2. Week 2 - Non-Linear Regression, OLS, and Log Loss
  4. 3. Week 3 - Neural Networks: ANNs, DNNs, and CNNs
  5. 4. Week 4 - Classification: SVMs, Naive Bayes, KNN and Decision Trees
  6. 5. Week 5 - Finishing Classification & Intro to Unsupervised Learning: Clustering & Dimensional Reduction

UCSD CSE151A Summer Session I 2024

Week 4 - Classification: SVMs, Naive Bayes, KNN and Decision Trees

  • Deadlines:
    • Quiz 4 Due 7/28/2024
    • Homework 3 Due 7/28/2024

Week 4 Lecture Material

  • Lecture Slides
    • Slides PDF Convolutions
    • Slides PDF SVMs
    • Slides PDF Naive Bayes
    • Slides PDF Decision Trees
  • Notebooks
    • Convolution Notebook
    • BCC Data Notebook
    • SVM Notebook
    • Decision Tree Notebook

Week 4 Discussion

  • Discussion Slides
  • Discussion Notebook