Search Results for "matlab project"
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Showing 12 open source projects for "matlab project"
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Machine Learning Homework
Matlab Coding homework for Machine Learning
...It may contain comments, example datasets, and perhaps test scripts. The repository does not seem to be heavily maintained as a software project; rather, it functions as a library of solved problems and educational examples. The project is useful if you want working MATLAB examples of classic ML techniques, to study, adapt, or compare with your own implementations. -
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Coursera Machine Learning
Coursera Machine Learning By Prof. Andrew Ng
CourseraMachineLearning is a personal collection of resources, notes, and programming exercises from Andrew Ng’s popular Machine Learning course on Coursera. It consolidates lecture references, programming tutorials, test cases, and supporting materials into one repository for easier review and practice. The project highlights fundamental machine learning concepts such as hypothesis functions, cost functions, gradient descent, bias-variance tradeoffs, and regression models. It also organizes... -
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This project aims to develop and share fast frequent subgraph mining and graph learning algorithms. Currently we release the frequent subgraph mining package FFSM and later we will include new functions for graph regression and classification package
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EEG Seizure Prediction
Seizure prediction from EEG data using machine learning
The Kaggle-EEG project is a machine learning solution developed for seizure prediction from EEG data, achieving 3rd place in the Kaggle/University of Melbourne Seizure Prediction competition. The repository processes EEG data to predict seizures by training machine learning models, specifically using SVM (Support Vector Machine) and RUS Boosted Tree ensemble models. The framework processes EEG data into features, trains models, and outputs predictions, handling temporal data to ensure accuracy. -
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nn22 Basic Neural Networks for Octave
Simple .m files, Basic Neural Networks study for Octave (or Matlab)
--> For a more detailed description check the README text under the 'Files' menu option :) The project consists of a few very simple .m files for a Basic Neural Networks study under Octave (or Matlab). The idea is to provide a context for beginners that will allow to develop neural networks, while at the same time get to see and feel the behavior of a basic neural networks' functioning. The code is completely open to be modified and may suit several scenarios. ... -
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Kernel Adaptive Filtering Toolbox
a Matlab benchmarking toolbox for kernel adaptive filtering
[Note: This project has moved. Visit https://github.com/steven2358/kafbox/ for the latest version.] A Matlab benchmarking toolbox for kernel adaptive filtering. Kernel adaptive filtering algorithms are online and adaptive regression algorithms based on kernels. They are suitable for nonlinear filtering, prediction, tracking and nonlinear regression in general. -
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CvHMM
Discrete Hidden Markov Models based on OpenCV
This project (CvHMM) is an implementation of discrete Hidden Markov Models (HMM) based on OpenCV. It is simple to understand and simple to use. The Zip file contains one header for the implementation and one main.cpp file for a demonstration of how it works. Hope it becomes useful for your projects. -
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This project is devoted to the creation of an open source Error-Correcting Output Codes (ECOC) library for the Machine Learning community. The ECOC framework is a powerful tool to deal with multi-class categorization problems.
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This project applies an interpretation of a k-NN algorithm to a library of GPS commuter data for speed prediction. The overall goal is to lay the foundation for a power management protocol for use in electric vehicles with hybrid energy storage.
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The Python Computer Vision Framework is an opened project deisgned for all those interested in computer vision. It aims at making computer vision more easy and structured and matlab-free. It may also be used for other artistic and scientific areas.
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The project goal is to develop several IP cores that would implement artificial neural networks using FPGA resources. These cores will be designed in such a way to allow easy integration in the Xilinx EDK framework.
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