Unsupervised Learning

Data Mining

Welcome
Vectors and Matrices
Introduction to Tensors
Advanced NumPy
Introduction to Pandas
Data Preparation and Wrangling
Exploratory Data Analysis (EDA)
- 6.1 Matplotlib and Seaborn
Midterm
Linear Regression
- 8.1 Classical Machine Learning
- 8.2 Linear Regression (Ordinary Least Squares)
Logistic Regression
- 9.1 Binary Logistic Regression
- 9.2 Multinomial Logistic Regression
Support Vector Machines
- 10.1 Polynomial Logistic Regression
- 10.2 Support Vector Machines
Kernel Methods
- 11.1 K Nearest Neighbors
Tree-based Models
- 12.1 Decision Trees
- 12.2 Ensemble Models
Unsupervised Learning
- 11.2 Clustering
Homeworks
Labs
- Lab 1
- Lab 2
- Lab 3
- Lab 4
- Lab 5
- Lab 6
- Lab 7
- Lab 8
- Lab 9
- Lab 10
- Lab 11
- Lab 12
References

Unsupervised Learning

“Education is the ability to listen to almost anything without losing your temper or your self-confidence.”
– Robert Frost

12.2 Ensemble Models

11.2 Clustering