Showing 8 open source projects for "real"

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  • 1
    X's Recommendation Algorithm

    X's Recommendation Algorithm

    Source code for the X Recommendation Algorithm

    ...Written primarily in Scala, it shows the architecture of large-scale recommendation systems, including candidate sourcing, ranking, and heuristics. 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: 2 This Week
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  • 2
    Pythonic Data Structures and Algorithms

    Pythonic Data Structures and Algorithms

    Minimal examples of data structures and algorithms in Python

    ...Because it’s in pure Python, it’s easy to read and modify, making it accessible even to those with modest programming experience. The repo helps bridge the gap between theoretical algorithm descriptions and real-world code, giving concrete, working implementations that one can study, debug, or extend.
    Downloads: 0 This Week
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  • 3
    Real-ESRGAN

    Real-ESRGAN

    Real-ESRGAN aims at developing Practical Algorithms

    Real-ESRGAN is a highly popular open-source project that provides practical algorithms for general image and video restoration using deep learning-based super-resolution techniques. It extends the original Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) approach by training on synthetic degradations to make results more robust on real-world images, effectively enhancing resolution, reducing noise/artifacts, and reconstructing fine detail in low-quality imagery. ...
    Downloads: 218 This Week
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  • 4
    GFPGAN

    GFPGAN

    GFPGAN aims at developing Practical Algorithms

    ...So that it can run in Windows or on CPU mode. GFPGAN aims at developing a Practical Algorithm for Real-world Face Restoration. It leverages rich and diverse priors encapsulated in a pretrained face GAN (e.g., StyleGAN2) for blind face restoration. Add V1.3 model, which produces more natural restoration results, and better results on very low-quality / high-quality inputs.
    Downloads: 67 This Week
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  • 5
    AlphaTensor

    AlphaTensor

    AI discovers faster, efficient algorithms for matrix multiplication

    ...The repository is organized into four main components: algorithms, benchmarking, nonequivalence, and recombination. These contain implementations of the discovered matrix multiplication algorithms, tools to benchmark their real-world performance, proofs of nonequivalence among thousands of solutions, and methods for decomposing larger problems into smaller factorizations. Users can explore AlphaTensor’s discovered algorithms interactively using Colab notebooks or Python scripts.
    Downloads: 1 This Week
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  • 6
    Consistent Depth

    Consistent Depth

    We estimate dense, flicker-free, geometrically consistent depth

    ...This approach achieves improved geometric consistency and visual stability compared to prior monocular reconstruction methods. The project can process challenging hand-held video footage, including those with moderate dynamic motion, making it practical for real-world usage.
    Downloads: 0 This Week
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  • 7
    FuzzyWuzzy

    FuzzyWuzzy

    Fuzzy string matching in Python

    ...Of course, a big problem with most corners of the internet is labeling. One of our most consistently frustrating issues is trying to figure out whether two ticket listings are for the same real-life event (that is, without enlisting the help of our army of interns). To pick an example completely at random, Cirque du Soleil has a show running in New York called “Zarkana”. When we scour the web to find tickets for sale, mostly those tickets are identified by a title, date, time, and venue. We’ve built up a library of “fuzzy” string matching routines to help us along. ...
    Downloads: 3 This Week
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  • 8

    Distant Speech Recognition

    Beamforming and Speech Recognition Toolkit

    BTK contains C++ and Python libraries that implement speech processing and microphone array techniques such as speech feature extraction, speech enhancement, speaker tracking, beamforming, dereverberation and echo cancellation algorithms. The Millennium ASR provides C++ and python libraries for automatic speech recognition. The Millennium ASR implements a weighted finite state transducer (WFST) decoder, training and adaptation methods. These toolkits are meant for facilitating research and...
    Downloads: 0 This Week
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