📗 -> Machine Learning
short mode
not done
tags include #class
description includes ML🔗 Critical Links
- Put important links for class
🔶 Course Description
Introduction to machine learning. Supervised and unsupervised learning, including classification, dimensionality reduction, regression, and clustering using modern machine learning methods. Applications of machine learning to other fields.
❗ Important
Instructor:
- Ilias Tagkopoulos - iliast@ucdavis.edu
TA:
- Trevor Chan (tchchan@ucdavis.edu)
- Pranav Gupta (pgpt@ucdavis.edu)
📄 Class Material
Week 1 - Course Intro
Week 2 - Regression & Regularization
- Regression and Regularization - ECS171-L3
Week 3 - Logistic Regression, Classification
Discussion on hw1 code
Week 4 - ANN Intro
Week 5 - DL and Naive Bayes
Week 6 - Decision Trees
Week 7 - SVMs
Week 8 - Unsupervised Learning
Veterans Day Holiday
Week 9 - Dimensionality Reduction and Clustering
Week 10 - Project Presentation
Thanksgiving Holiday