4 projects for "artificial neural network python" with 2 filters applied:

  • Gen AI apps are built with MongoDB Atlas Icon
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  • 1
    AudioCraft

    AudioCraft

    Audiocraft is a library for audio processing and generation

    AudioCraft is a PyTorch library for text-to-audio and text-to-music generation, packaging research models and tooling for training and inference. It includes MusicGen for music generation conditioned on text (and optionally melody) and AudioGen for text-conditioned sound effects and environmental audio. Both models operate over discrete audio tokens produced by a neural codec (EnCodec), which acts like a tokenizer for waveforms and enables efficient sequence modeling. The repo provides...
    Downloads: 2 This Week
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  • 2
    PyTorch3D

    PyTorch3D

    PyTorch3D is FAIR's library of reusable components for deep learning

    PyTorch3D is a comprehensive library for 3D deep learning that brings differentiable rendering, geometric operations, and 3D data structures into the PyTorch ecosystem. It’s designed to make it easy to build and train neural networks that work directly with 3D data such as meshes, point clouds, and implicit surfaces. The library provides fast GPU-accelerated implementations of rendering pipelines, transformations, rasterization, and lighting—making it possible to compute gradients through full...
    Downloads: 0 This Week
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  • 3
    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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  • 4
    TensorFlow Course

    TensorFlow Course

    Simple and ready-to-use tutorials for TensorFlow

    This repository houses a highly popular (~16k stars) set of TensorFlow tutorials and example code aimed at beginners and intermediate users. It includes Jupyter notebooks and scripts that cover neural network fundamentals, model training, deployment, and more, with support for Google Colab.
    Downloads: 0 This Week
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