The codes are answer for lessons Machine Learning of Andrew NG.
Each main.m function has configuration you need to run all of the codes.
Linear Regression with Multiple Variables
Logistic Regression and Regularization
Neural Networks: Representation
Neural Networks: Learning
Advice for Applying Machine Learning
Support Vector Machines
Unsupervised Learning and Dimensionality Reduction
Anomaly Detection and Recommender Systems
Ex1, 100 Points, 16/05/2021
Ex2, 100 Points, 16/05/2021
Ex3, 100 Points, 23/05/2021
Ex4, 100 Points, 04/06/2021
Ex5, 100 Points, 07/06/2021
Ex6, 100 Points, 10/06/2021
Ex7, 100 Points, 11/06/2021
Ex8, 100 Points, 12/06/2021
Summary for Machine Learning Hosted by Andrew
The framework of machine learning05-05
Machine learning mathematics05-05
Backpropagation of Machine Learning05-07
How to solve the the problem of overfitting - Class review05-16
Machine learning questions06-04
How dose regularization work in ML and DL? - Class review06-06
How to debug your machine learning system06-08
What is support vector machine/SVM06-10
Unsupervised learning and clustering algorithms06-11
Dimensionality reduction for input data06-11
Anomaly Detection - Class Review06-12
Recommender Systems - Class Review06-12
Large Scale Machine Learning - Class Review06-13
Photo Optical Recognition/OCR - Class Review06-13
Andrew NG, Machine learning