Author: Taimingwang Liu

Syllabus

Lecture 01

Lecture 02 - PCA

Lecture 03 - Applications of PCA

Lecture 04 - K-Means Clustering & Logistic Regression

Lecture 05 - Naive Bayes & MLP-NNs

Lecture 06 - Decision Tree & Random Forest

Lecture 07 - SVM

Lecture 08 - Autoencoder for dimension reduction

Lecture 09 - Linear and Non-linear regression

Lecture 10 - Model Evaluation & Optimization, Supervised & Unsupervised Learning, Parametric & Non-parametric Classification Model

Review Meeting