Week 2
Eigenvalues and Eigenvectors
Data Mining
Welcome
Week 1: Vectors and Matrices
1.1 Scalars and Vectors
1.2 Vector Operations
1.3 Matrices
1.4 Matrix Operations
Practice Problems
Week 2
Eigenvalues and Eigenvectors
Week 3
1.1 Scalars and Vectors
Week 4
Week 5
Week 6
Week 7
Midterm
Week 8
8.1 Machine Learning
8.2 Modeling Methodology
Practice Problems
Week 9
9.1 Linear Models
9.2 Linear Regression
9.3 Regression Evaluation
Practice Problems
Week 10
10.1 Linear Models
10.2 Logistic Regression
10.2 Classification Evaluation
Practice Problems
Week 11
11.1 Tree Models
11.2 Decision Tree
Practice Problems
Week 12
12.1 Ensemble Models
12.2 Random Forest
Practice Problems
Week 13
13.1 Neighbors Models
13.2 K-Nearest Neighbors (KNN)
Practice Problems
Week 14
14.1 Support Vector Machines (SVM)
Practice Problems
Week 15
15.1 Clustering Models
15.2 K-Means
15.3 Clustering Evaluation
Practice Problems
Homeworks
Homework 1
Homework 2
Homework 3
References
Week 2
Eigenvalues and Eigenvectors
Eigenvalues and Eigenvectors
Week 2
Week 3