Open Source Windows Education Software

Browse free open source Education software and projects for Windows below. Use the toggles on the left to filter open source Education software by OS, license, language, programming language, and project status.

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  • 1

    AI Path

    AI Pathfinding Presentation

    Presentation of pathfinding algorithms Howto: 1. Create Map (manual or use Map -> Rapid Deployment) 2. Select start point 3. Select end point 4. Choose alg 5. Click Path -> Find
    Downloads: 0 This Week
    Last Update:
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  • 2
    Este proyecto constituye una adaptacion y mejora del codigo ANFIS de dominio público de Roger Jang. / This project is an adaptation and improvement of the original public domain ANFIS code of Roger Jang.
    Downloads: 0 This Week
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  • 3

    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.
    Downloads: 0 This Week
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  • 4
    A Java client for the Player/Stage robot platform.
    Downloads: 0 This Week
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  • 5
    A collection of open source software and documents on machine perception and machine learning. Includes a state of the art face detector (MPISearch), video labeling tools (Score), and tutorials (Kolmogorov Tutorials).
    Downloads: 0 This Week
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  • 6
    An open source face recognition project.
    Downloads: 0 This Week
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  • 7
    The ultimate Reinforcement Learning Simulator!!!
    Downloads: 0 This Week
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  • 8
    choco
    Choco is not hosted on sourceforge anymore. Please now visit http://choco-solver.org/ !
    Downloads: 0 This Week
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  • 9
    wav2letter++

    wav2letter++

    Facebook AI research's automatic speech recognition toolkit

    First, install Flashlight (using the 0.3 branch is required) with the ASR application. This repository includes recipes to reproduce the following research papers as well as pre-trained models. All results reproduction must use Flashlight <= 0.3.2 for exact reproducibility. At least one of LZMA, BZip2, or Z is required for LM compression with KenLM. It is highly recommended to build KenLM with position-independent code (-fPIC) enabled, to enable python compatibility. After installing, run export KENLM_ROOT_DIR=... so that wav2letter++ can find it. This is needed because KenLM doesn't support a make install step.wav2letter++ expects audio and transcription data to be prepared in a specific format so that they can be read from the pipelines. Each dataset (test/valid/train) needs to be in a separate file with one sample per line. A sample is specified using 4 columns separated by space (or tabs).
    Downloads: 0 This Week
    Last Update:
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