Showing 17 open source projects for "machine"

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  • 1
    The Algorithms Python

    The Algorithms Python

    All Algorithms implemented in Python

    ...Each implementation is designed with clarity in mind, favoring readability and comprehension over performance optimization. The project covers various domains including mathematics, cryptography, machine learning, sorting, graph theory, and more. With contributions from a large global community, it continually grows and improves through collaboration and peer review. This repository is an ideal reference for students, educators, and developers seeking hands-on experience with algorithmic concepts in Python.
    Downloads: 5 This Week
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  • 2
    PRML

    PRML

    PRML algorithms implemented in Python

    PRML repository is a respected and well-maintained project that implements the foundational algorithms from the famous textbook Pattern Recognition and Machine Learning by Christopher M. Bishop, providing a practical and accessible Python reference for both students and professionals. Rather than just summarizing concepts, the repository includes working code that demonstrates linear regression and classification, kernel methods, neural networks, graphical models, mixture models with EM algorithms, approximate inference, and sequential data methods — all following the book’s structure and notation. ...
    Downloads: 3 This Week
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  • 3
    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
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  • 4
    AStro inFER - a rule miner and executer
    Downloads: 0 This Week
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  • 5
    MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack
    Downloads: 0 This Week
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  • 6
    GFPGAN

    GFPGAN

    GFPGAN aims at developing Practical Algorithms

    GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration. Colab Demo for GFPGAN; (Another Colab Demo for the original paper model) Online demo: Huggingface (return only the cropped face) Online demo: Replicate.ai (may need to sign in, return the whole image). Online demo: Baseten.co (backed by GPU, returns the whole image). We provide a clean version of GFPGAN, which can run without CUDA extensions. So that it can run in Windows or on CPU mode. GFPGAN aims at developing...
    Downloads: 40 This Week
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  • 7
    Gym

    Gym

    Toolkit for developing and comparing reinforcement learning algorithms

    Gym by OpenAI is a toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents, everything from walking to playing games like Pong or Pinball. Open source interface to reinforce learning tasks. The gym library provides an easy-to-use suite of reinforcement learning tasks. Gym provides the environment, you provide the algorithm. You can write your agent using your existing numerical computation library, such as TensorFlow or Theano. It makes no...
    Downloads: 0 This Week
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  • 8
    Coach

    Coach

    Enables easy experimentation with state of the art algorithms

    Coach is a python framework that models the interaction between an agent and an environment in a modular way. With Coach, it is possible to model an agent by combining various building blocks, and training the agent on multiple environments. The available environments allow testing the agent in different fields such as robotics, autonomous driving, games and more. It exposes a set of easy-to-use APIs for experimenting with new RL algorithms and allows simple integration of new environments...
    Downloads: 0 This Week
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  • 9
    Active Learning

    Active Learning

    Framework and examples for active learning with machine learning model

    ...It includes several established active learning strategies such as uncertainty sampling, k-center greedy selection, and bandit-based methods, while also allowing for custom algorithm implementations. The framework integrates with both classical machine learning models (SVM, logistic regression) and neural networks.
    Downloads: 3 This Week
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  • 10
    SteppedStateMachine

    SteppedStateMachine

    Creates and operates a stepped state machine

    Implements a stepped state machine, i.e. a state machine which executes a single state transition at a time. Because of this, no data, e.g. state data, can be stored between executions. Instead, any such data must be stored in persistent storage between executions. This permits operation of the state machine as a CGI program in a web server. A WSGI or fastCGI or other such web server is not required.
    Downloads: 0 This Week
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  • 11

    MarketSim

    A python based auction market simulator for agricultural trade

    The market assumes an environment in which farmers sell their produce through brokers and traders locate produce to buy through brokers. The major aim of the simulator is to experiment with various reputation mechanisms to manage bottlenecks and to model various adversarial scenarios. The market is aimed to simulate agricultural trade in developing countries. It is written in python and mysql database on Linux.
    Downloads: 0 This Week
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  • 12

    PyVision Computer Vision Toolkit

    A Python computer vision library

    PyVision is a object-oriented Computer Vision Toolkit for researchers that contains vision and machine learning algorithms and algorithm analysis and easily interfaces with scipy/numpy, PIL, opencv and other computer and machine learning libraries.
    Downloads: 0 This Week
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  • 13

    ProximityForest

    Efficient Approximate Nearest Neighbors for General Metric Spaces

    A proximity forest is a data structure that allows for efficient computation of approximate nearest neighbors of arbitrary data elements in a metric space. See: O'Hara and Draper, "Are You Using the Right Approximate Nearest Neighbor Algorithm?", WACV 2013 (best student paper award). One application of a ProximityForest is given in the following CVPR publication: Stephen O'Hara and Bruce A. Draper, "Scalable Action Recognition with a Subspace Forest," IEEE Conference on Computer...
    Downloads: 0 This Week
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  • 14

    ktree

    clustering, machine learning, algorithms

    This project has moved to github at http://lmwtree.devries.ninja.
    Downloads: 0 This Week
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  • 15
    This program generates customizable hyper-surfaces (multi-dimensional input and output) and samples data from them to be used further as benchmark for response surface modeling tasks or optimization algorithms.
    Downloads: 0 This Week
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  • 16
    A threaded Web graph (Power law random graph) generator written in Python. It can generate a synthetic Web graph of about one million nodes in a few minutes on a desktop machine. It implements a threaded variant of the RMAT algorithm.
    Downloads: 0 This Week
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  • 17

    Firefly's Clean Lzo

    A human-readable ISC-Licensed implementation of the LZO1X algorithm.

    ...The main problem with LZO is that it is absolutely not human readable. People have done crazy stuff to get LZO to run in their language. Usually it implies inline assembly or trying to execute data which actually contains machine code. This is sick. Whoever is responsible for this sorry situation ought to be ashamed. So I'm going to deobfuscate LZO and provide a ISC implementation of this algorithm in Python and C. In addition, I will provide a textual description of the algorithm so that it can be easily ported to any programming language. I expect a severe performance degradation, but I leave optimizing for speed to other people.
    Downloads: 0 This Week
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