Showing 395 open source projects for "neural networks"

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  • 1
    Tiny CUDA Neural Networks

    Tiny CUDA Neural Networks

    Lightning fast C++/CUDA neural network framework

    This is a small, self-contained framework for training and querying neural networks. Most notably, it contains a lightning-fast "fully fused" multi-layer perceptron (technical paper), a versatile multiresolution hash encoding (technical paper), as well as support for various other input encodings, losses, and optimizers. We provide a sample application where an image function (x,y) -> (R,G,B) is learned. The fully fused MLP component of this framework requires a very large amount of shared...
    Downloads: 0 This Week
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  • 2
    Stock prediction deep neural learning

    Stock prediction deep neural learning

    Predicting stock prices using a TensorFlow LSTM

    Predicting stock prices can be a challenging task as it often does not follow any specific pattern. However, deep neural learning can be used to identify patterns through machine learning. One of the most effective techniques for series forecasting is using LSTM (long short-term memory) networks, which are a type of recurrent neural network (RNN) capable of remembering information over a long period of time. This makes them extremely useful for predicting stock prices. Predicting stock prices...
    Downloads: 5 This Week
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  • 3
    PyTorch

    PyTorch

    Open source machine learning framework

    PyTorch is a Python package that offers Tensor computation (like NumPy) with strong GPU acceleration and deep neural networks built on tape-based autograd system. This project allows for fast, flexible experimentation and efficient production. PyTorch consists of torch (Tensor library), torch.autograd (tape-based automatic differentiation library), torch.jit (a compilation stack [TorchScript]), torch.nn (neural networks library), torch.multiprocessing (Python multiprocessing), and torch.utils...
    Downloads: 123 This Week
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  • 4
    Keras

    Keras

    Python-based neural networks API

    Python Deep Learning library
    Downloads: 31 This Week
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    Stockfish

    Stockfish

    UCI chess engine

    ... is open source (GPLv3 license). That means you can read the code, modify it, and contribute back. You can use Stockfish on your computer or on your iOS or Android device. So you can get world-class chess analysis, wherever you are. The Stockfish engine features two evaluation functions for chess, the classical evaluation based on handcrafted terms, and the NNUE evaluation based on efficiently updatable neural networks.
    Downloads: 56 This Week
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  • 6
    ncnn

    ncnn

    High-performance neural network inference framework for mobile

    ncnn is a high-performance neural network inference computing framework designed specifically for mobile platforms. It brings artificial intelligence right at your fingertips with no third-party dependencies, and speeds faster than all other known open source frameworks for mobile phone cpu. ncnn allows developers to easily deploy deep learning algorithm models to the mobile platform and create intelligent APPs. It is cross-platform and supports most commonly used CNN networks, including...
    Downloads: 8 This Week
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  • 7
    DeepVariant

    DeepVariant

    DeepVariant is an analysis pipeline that uses a deep neural networks

    ... extends DeepVariant's functionality, allowing it to utilize the power of neural networks to predict genomic variants in trios or duos. See this page for more details and instructions on how to run DeepTrio. Out-of-the-box use for PCR-positive samples and low quality sequencing runs, and easy adjustments for different sequencing technologies and non-human species.
    Downloads: 6 This Week
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  • 8
    Image-Editor

    Image-Editor

    AI based photo editing website for changing image background

    ...' with the name of your choice. Image-Editor uses Python's cv2 library, which provides an easy and efficient way to work with images and videos, including a wide range of image processing and computer vision algorithms. With cv2, you can easily read, write, filter, and display images, and much more. Image-Editor uses Mediapipe's selfie_segmentation model for background removal in real-time video streams. This advanced model uses deep neural networks to detect and remove the background.
    Downloads: 9 This Week
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  • 9
    Machine Learning PyTorch Scikit-Learn

    Machine Learning PyTorch Scikit-Learn

    Code Repository for Machine Learning with PyTorch and Scikit-Learn

    Initially, this project started as the 4th edition of Python Machine Learning. However, after putting so much passion and hard work into the changes and new topics, we thought it deserved a new title. So, what’s new? There are many contents and additions, including the switch from TensorFlow to PyTorch, new chapters on graph neural networks and transformers, a new section on gradient boosting, and many more that I will detail in a separate blog post. For those who are interested in knowing what...
    Downloads: 48 This Week
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  • 10
    Sonnet

    Sonnet

    TensorFlow-based neural network library

    Sonnet is a neural network library built on top of TensorFlow designed to provide simple, composable abstractions for machine learning research. Sonnet can be used to build neural networks for various purposes, including different types of learning. Sonnet’s programming model revolves around a single concept: modules. These modules can hold references to parameters, other modules and methods that apply some function on the user input. There are a number of predefined modules that already ship...
    Downloads: 2 This Week
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  • 11
    Hello AI World

    Hello AI World

    Guide to deploying deep-learning inference networks

    Hello AI World is a great way to start using Jetson and experiencing the power of AI. In just a couple of hours, you can have a set of deep learning inference demos up and running for realtime image classification and object detection on your Jetson Developer Kit with JetPack SDK and NVIDIA TensorRT. The tutorial focuses on networks related to computer vision, and includes the use of live cameras. You’ll also get to code your own easy-to-follow recognition program in Python or C++, and train...
    Downloads: 6 This Week
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  • 12
    AI Upscaler for Blender

    AI Upscaler for Blender

    AI Upscaler for Blender using Real-ESRGAN

    ... on the CPU. Blender renders a low-resolution image. The Real-ESRGAN Upscaler upscales the low-resolution image to a higher-resolution image. Real-ESRGAN is a deep learning upscaler that uses neural networks to achieve excellent results by adding in detail when it upscales.
    Downloads: 5 This Week
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  • 13
    Ludwig AI

    Ludwig AI

    Low-code framework for building custom LLMs, neural networks

    Declarative deep learning framework built for scale and efficiency. Ludwig is a low-code framework for building custom AI models like LLMs and other deep neural networks. Declarative YAML configuration file is all you need to train a state-of-the-art LLM on your data. Support for multi-task and multi-modality learning. Comprehensive config validation detects invalid parameter combinations and prevents runtime failures. Automatic batch size selection, distributed training (DDP, DeepSpeed...
    Downloads: 2 This Week
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  • 14
    Albumentations

    Albumentations

    Fast image augmentation library and an easy-to-use wrapper

    Albumentations is a computer vision tool that boosts the performance of deep convolutional neural networks. Albumentations is a Python library for fast and flexible image augmentations. Albumentations efficiently implements a rich variety of image transform operations that are optimized for performance, and does so while providing a concise, yet powerful image augmentation interface for different computer vision tasks, including object classification, segmentation, and detection. Albumentations...
    Downloads: 2 This Week
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  • 15
    InvertibleNetworks.jl

    InvertibleNetworks.jl

    A Julia framework for invertible neural networks

    Building blocks for invertible neural networks in the Julia programming language.
    Downloads: 0 This Week
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  • 16
    T81 558

    T81 558

    Applications of Deep Neural Networks

    Deep learning is a group of exciting new technologies for neural networks. Through a combination of advanced training techniques and neural network architectural components, it is now possible to create neural networks that can handle tabular data, images, text, and audio as both input and output. Deep learning allows a neural network to learn hierarchies of information in a way that is like the function of the human brain. This course will introduce the student to classic neural network...
    Downloads: 0 This Week
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  • 17
    pytorch-cpp

    pytorch-cpp

    C++ Implementation of PyTorch Tutorials for Everyone

    C++ Implementation of PyTorch Tutorials for Everyone. This repository provides tutorial code in C++ for deep learning researchers to learn PyTorch (i.e. Section 1 to 3) Interactive Tutorials are currently running on LibTorch Nightly Version. Libtorch only supports 64bit Windows and an x64 generator needs to be specified. Create all required script module files for pre-learned models/weights during the build. Requires installed python3 with PyTorch and torch-vision. You can choose to only...
    Downloads: 1 This Week
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  • 18
    oneDNN

    oneDNN

    oneAPI Deep Neural Network Library (oneDNN)

    This software was previously known as Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN) and Deep Neural Network Library (DNNL). oneAPI Deep Neural Network Library (oneDNN) is an open-source cross-platform performance library of basic building blocks for deep learning applications. oneDNN is part of oneAPI. The library is optimized for Intel(R) Architecture Processors, Intel Processor Graphics and Xe Architecture graphics. oneDNN has experimental support for the following...
    Downloads: 1 This Week
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  • 19
    Alpa

    Alpa

    Training and serving large-scale neural networks

    Alpa is a system for training and serving large-scale neural networks. Scaling neural networks to hundreds of billions of parameters has enabled dramatic breakthroughs such as GPT-3, but training and serving these large-scale neural networks require complicated distributed system techniques. Alpa aims to automate large-scale distributed training and serving with just a few lines of code.
    Downloads: 0 This Week
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  • 20
    DeepLabCut

    DeepLabCut

    Implementation of DeepLabCut

    DeepLabCut™ is an efficient method for 2D and 3D markerless pose estimation based on transfer learning with deep neural networks that achieves excellent results (i.e. you can match human labeling accuracy) with minimal training data (typically 50-200 frames). We demonstrate the versatility of this framework by tracking various body parts in multiple species across a broad collection of behaviors. The package is open source, fast, robust, and can be used to compute 3D pose estimates...
    Downloads: 2 This Week
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  • 21
    SciMLBenchmarks.jl

    SciMLBenchmarks.jl

    Benchmarks for scientific machine learning (SciML) software

    SciMLBenchmarks.jl holds webpages, pdfs, and notebooks showing the benchmarks for the SciML Scientific Machine Learning Software ecosystem.
    Downloads: 0 This Week
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  • 22
    ktrain

    ktrain

    ktrain is a Python library that makes deep learning AI more accessible

    ktrain is a Python library that makes deep learning and AI more accessible and easier to apply. ktrain is a lightweight wrapper for the deep learning library TensorFlow Keras (and other libraries) to help build, train, and deploy neural networks and other machine learning models. Inspired by ML framework extensions like fastai and ludwig, ktrain is designed to make deep learning and AI more accessible and easier to apply for both newcomers and experienced practitioners. With only a few lines...
    Downloads: 1 This Week
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  • 23
    NNlib.jl

    NNlib.jl

    Neural Network primitives with multiple backends

    This package provides a library of functions useful for neural networks, such as softmax, sigmoid, batched multiplication, convolutions and pooling. Many of these are used by Flux.jl, which loads this package, but they may be used independently.
    Downloads: 0 This Week
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  • 24
    Chainer

    Chainer

    A flexible deep learning framework

    Chainer is a Python-based deep learning framework. It provides automatic differentiation APIs based on dynamic computational graphs as well as high-level APIs for neural networks.
    Downloads: 0 This Week
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  • 25
    The SpeechBrain Toolkit

    The SpeechBrain Toolkit

    A PyTorch-based Speech Toolkit

    SpeechBrain is an open-source and all-in-one conversational AI toolkit. It is designed to be simple, extremely flexible, and user-friendly. Competitive or state-of-the-art performance is obtained in various domains. SpeechBrain supports state-of-the-art methods for end-to-end speech recognition, including models based on CTC, CTC+attention, transducers, transformers, and neural language models relying on recurrent neural networks and transformers. Speaker recognition is already deployed...
    Downloads: 1 This Week
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