Showing 10 open source projects for "python q learning"

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  • 1
    Smile

    Smile

    Statistical machine intelligence and learning engine

    Smile is a fast and comprehensive machine learning engine. With advanced data structures and algorithms, Smile delivers the state-of-art performance. Compared to this third-party benchmark, Smile outperforms R, Python, Spark, H2O, xgboost significantly. Smile is a couple of times faster than the closest competitor. The memory usage is also very efficient. If we can train advanced machine learning models on a PC, why buy a cluster?
    Downloads: 0 This Week
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  • 2
    Tribuo

    Tribuo

    Tribuo - A Java machine learning library

    Tribuo* is a machine learning library written in Java. It provides tools for classification, regression, clustering, model development, and more. It provides a unified interface to many popular third-party ML libraries like xgboost and liblinear. With interfaces to native code, Tribuo also makes it possible to deploy models trained by Python libraries (e.g. scikit-learn, and pytorch) in a Java program.
    Downloads: 1 This Week
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  • 3
    Ceka

    Ceka

    Crowd Environment and its Knowledge Analysis

    A knowledge analysis tool for crowdsourcing based on Weka. We also have a Python version of Crowdsourcing Learning: CrowdwiseKit on GitHub (https://github.com/tssai-lab/CrowdwiseKit).
    Downloads: 0 This Week
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  • 4
    ModelDB

    ModelDB

    Open Source ML Model Versioning, Metadata, and Experiment Management

    An open-source system for Machine Learning model versioning, metadata, and experiment management. ModelDB is an open-source system to version machine learning models including their ingredients code, data, config, and environment and to track ML metadata across the model lifecycle.
    Downloads: 0 This Week
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  • 5
    The Teachingbox uses advanced machine learning techniques to relieve developers from the programming of hand-crafted sophisticated behaviors of autonomous agents (such as robots, game players etc...) In the current status we have implemented a well founded reinforcement learning core in Java with many popular usecases, environments, policies and learners. Obtaining the teachingbox: FOR USERS: If you want to download the latest releases, please visit:...
    Downloads: 1 This Week
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  • 6
    DSTK - DataScience ToolKit

    DSTK - DataScience ToolKit

    DSTK - DataScience ToolKit for All of Us

    DSTK - DataScience ToolKit is an opensource free software for statistical analysis, data visualization, text analysis, and predictive analytics. Newer version and smaller file size can be found at: https://sourceforge.net/projects/dstk3/ It is designed to be straight forward and easy to use, and familar to SPSS user. While JASP offers more statistical features, DSTK tends to be a broad solution workbench, including text analysis and predictive analytics features. Of course you may specify...
    Downloads: 0 This Week
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  • 7
    H2O-3

    H2O-3

    H2O is an Open Source, Distributed, Fast & Scalable Machine Learning

    H2O-3 is an open-source machine learning platform designed to build scalable and distributed machine learning models across large datasets. The system operates as an in-memory computing platform that allows data scientists to train models quickly using distributed resources. It supports many machine learning algorithms including generalized linear models, gradient boosting machines, deep learning networks, and ensemble techniques.
    Downloads: 0 This Week
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  • 8
    openModeller is a complete C++ framework for species potential distribution modelling. The project also includes a graphical user interface, a web service interface and an API for Python.
    Downloads: 6 This Week
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  • 9
    Ms. Pac-Man Framework

    Ms. Pac-Man Framework

    Using reinforcement learning with relative input to train Ms. Pac-Man

    This Java-application contains all required components to simulate a game of Ms. Pac-Man and let an agent learn intelligent playing behaviour using reinforcement learning and either Q-Learning or SARSA. The framework was developed by Luuk Bom and Ruud Henken, under supervision of Marco Wiering, Department of Artificial Intelligence, University of Groningen. It formed the basis of a bachelor's thesis titled "Using reinforcement learning with relative input to train Ms. Pac-Man", L.A.M. Bom (2012).
    Downloads: 0 This Week
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  • 10
    This project consists in a set of challenges to recognize images acquired from 3d Lasers.
    Downloads: 0 This Week
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