Showing 8 open source projects for "q learning algorithm"

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  • 1
    Hello Algorithm

    Hello Algorithm

    Animated illustrations, one-click data structure

    Animated illustrations, one-click data structure and algorithm tutorials. This project aims to create an open source, free, novice-friendly introductory tutorial on data structures and algorithms. The whole book uses animated illustrations, the content is clear and easy to understand, and the learning curve is smooth, guiding beginners to explore the knowledge map of data structures and algorithms.
    Downloads: 10 This Week
    Last Update:
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  • 2
    X's Recommendation Algorithm

    X's Recommendation Algorithm

    Source code for the X Recommendation Algorithm

    ...While certain components (such as safety layers, spam detection, or private data) are excluded, the release provides valuable insights into the design of real-world machine learning–driven ranking systems. The project is intended as a reference for researchers, developers, and the public to study, experiment with, and better understand the mechanisms behind social media content.
    Downloads: 1 This Week
    Last Update:
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  • 3
    hello-algorithm

    hello-algorithm

    Algorithm training for Xiaobai

    hello-algorithm is an educational repository designed to teach data structures and algorithms through clear explanations, visualizations, and code examples. It provides a structured learning path that covers fundamental concepts such as arrays, linked lists, trees, graphs, sorting algorithms, and dynamic programming. The project emphasizes understanding over memorization by breaking down complex topics into intuitive explanations supported by diagrams and examples.
    Downloads: 0 This Week
    Last Update:
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  • 4
    java-string-similarity

    java-string-similarity

    Implementation of various string similarity and distance algorithms

    Implementation of various string similarity and distance algorithms: Levenshtein, Jaro-winkler, n-Gram, Q-Gram, Jaccard index, Longest Common Subsequence edit distance, cosine similarity. A library implementing different string similarity and distance measures. A dozen of algorithms (including Levenshtein edit distance and sibblings, Jaro-Winkler, Longest Common Subsequence, cosine similarity etc.) are currently implemented. The main characteristics of each implemented algorithm are presented below. ...
    Downloads: 12 This Week
    Last Update:
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  • 5

    OpenDino

    Open Source Java platform for Optimization, DoE, and Learning.

    OpenDino is an open source Java platform for optimization, design of experiment and learning. It provides a graphical user interface (GUI) and a platform which simplifies integration of new algorithms as "Modules". Implemented Modules Evolutionary Algorithms: - CMA-ES - (1+1)-ES - Differential Evolution Deterministic optimization algorithm: - SIMPLEX Learning: - a simple Artificial Neural Net Optimization problems: - test functions - interface for executing other programs (solvers) - parallel execution of problems - distributed execution of problems via socket connection between computers Others: - data storage - data analyser and viewer
    Downloads: 0 This Week
    Last Update:
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  • 6
    The Free Connectionist Q-learning Java Framework is an library for developing learning systems. Keywords: qlearning, artificial intelligence, alife, neural nets, neural networks, machine learning, reinforcement learning unsupervised learning agents lejos
    Downloads: 1 This Week
    Last Update:
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  • 7
    KNN-WEKA provides a implementation of the K-nearest neighbour algorithm for Weka. Weka is a collection of machine learning algorithms for data mining tasks. For more information on Weka, see http://www.cs.waikato.ac.nz/ml/weka/.
    Downloads: 0 This Week
    Last Update:
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  • 8
    A Java implementation of the NEAT algorithm as created by Kenneth O Stanley. Also provides a toolkit for further experiments to be created and can provide both local and distributed learning environments.
    Downloads: 0 This Week
    Last Update:
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