🤖 MatLab/Octave examples of popular machine learning algorithms with code examples and mathematics being explained
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Updated
Jul 8, 2020 - MATLAB
🤖 MatLab/Octave examples of popular machine learning algorithms with code examples and mathematics being explained
Learning a Single Convolutional Super-Resolution Network for Multiple Degradations (CVPR, 2018) (Matlab)
GPstuff - Gaussian process models for Bayesian analysis
A MATLAB implementation of the TensorFlow Neural Networks Playground seen on http://playground.tensorflow.org/
Code for paper "A Distributed ADMM Approach for Collaborative Regression Learning in Edge Computing"
multivariate Gaussian process regression and multivariate Student-t process regression
Code to implement efficient spatio-temporal Gaussian Process regression via iterative Kalman Filtering. KF is used to resolve the temporal part of the space-time process while, standard GP regression is used for the spatial part
MATLAB code for Relevance Vector Machine using SB2_Release_200.
Machine Learning Course by Stanford on Coursera (Andrew Ng)
Interactive courseware module that addresses the fundamentals of regression analysis taught in STEM courses.
Project Page of Combining 3D Morphable Models: A Large scale Face-and-Head Model - [CVPR 2019]
An ANFIS Model for Stock Price Prediction
Interactive courseware module that introduces typical workflow, setup, and considerations involved in solving regression problems with machine learning.
Gaussian Process Regression using GPML toolbox
Predicting solar generation based on weather forecast - a project which was part of Machine Learning course at BITS Pilani
Integrative Reduced Rank Regression with Multi-View Predictors
Implementation of Fast Orthogonal Search (FOS) Algorithm in MATLAB
Matlab source code of the paper "D. Wu and J.M. Mendel, Patch Learning, IEEE Trans. on Fuzzy Systems, 28(9):1996-2008, 2020"
Matlab code of the IRD algorithm in the paper: 刘子昂, 蒋雪, 伍冬睿, "基于池的无监督线性回归主动学习," 自动化学报, 2020. Or the English version here: https://arxiv.org/pdf/2001.05028.pdf
Clustering and segmentation of heterogeneous functional data (sequential data) with regime changes by mixture of Hidden Markov Model Regressions (MixFHMMR) and the EM algorithm
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