🤖 MatLab/Octave examples of popular machine learning algorithms with code examples and mathematics being explained

Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means

MATLAB/Octave library for stochastic optimization algorithms: Version 1.0.20

机器学习-Coursera-吴恩达- python+Matlab代码实现

A MATLAB toolbox for classifier: Version 1.0.7

Matlab library for gradient descent algorithms: Version 1.0.1

A matlab EEG toolbox to perform overlap correction and non-linear & linear regression.

Dynamic movement primitives (DMPs) are a method of trajectory control/planning from Stefan Schaal’s lab. Complex movements have long been thought to be composed of sets of primitive action ‘building blocks’ executed in sequence and \ or in parallel, and DMPs are a proposed mathematical formalization of these primitives. The difference between DM…

My lecture notes and assignment solutions for the Coursera machine learning class taught by Andrew Ng.

Variational Bayes linear and logistic regression

In this work, we use convex optimization package in MATLAB to implement multi-user transmit beamforming problem and linear regression. This is the homework 2 of ELEC 5470 Convex Optimization, HKUST.

Project on blood pressure estimation from ECG and PPG signals.

# Machine Learning (Coursera) This is my solution to all the programming assignments and quizzes of Machine-Learning (Coursera) taught by Andrew Ng. After completing this course you will get a broad idea of Machine learning algorithms. Try to solve all the assignments by yourself first, but if you get stuck somewhere then feel free to browse the…

💡This repository contains all of the lecture exercises of Machine Learning course by Andrew Ng, Stanford University @ Coursera. All are implemented by myself and in MATLAB/Octave.

MATLAB implementation of Gradient Descent algorithm for Multivariate Linear Regression

Finding evidence for the existence of Strange, non-chaotic attractors in the Quasi-periodically driven duffing oscillator.

Andrew Ng's Machine Learning Course

Stanford's Machine Learning Exercises

Source code of generalized shuffled linear regression

Machine Learning Exercises from Online Course (Coursera)