Showing 37 open source projects for "computer based training"

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  • 1
    deep-learning-for-image-processing

    deep-learning-for-image-processing

    deep learning for image processing including classification

    deep-learning-for-image-processing is an extensive educational repository covering practical deep learning methods for computer vision. It organizes implementations, explanations, presentation files, and video lessons around major neural network architectures. The material teaches both model structure and training workflows, with examples built in PyTorch and TensorFlow through Keras. Classification topics range from LeNet and AlexNet to ResNet, EfficientNet, Vision Transformer, Swin Transformer, ConvNeXt, and MobileViT. ...
    Downloads: 10 This Week
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  • 2
    Gluon CV Toolkit

    Gluon CV Toolkit

    Gluon CV Toolkit

    GluonCV provides implementations of state-of-the-art (SOTA) deep learning algorithms in computer vision. It aims to help engineers, researchers, and students quickly prototype products, validate new ideas and learn computer vision. It features training scripts that reproduce SOTA results reported in latest papers, a large set of pre-trained models, carefully designed APIs and easy-to-understand implementations and community support.
    Downloads: 0 This Week
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  • 3
    GIMP ML

    GIMP ML

    AI for GNU Image Manipulation Program

    This repository introduces GIMP3-ML, a set of Python plugins for the widely popular GNU Image Manipulation Program (GIMP). It enables the use of recent advances in computer vision to the conventional image editing pipeline. Applications from deep learning such as monocular depth estimation, semantic segmentation, mask generative adversarial networks, image super-resolution, de-noising and coloring have been incorporated with GIMP through Python-based plugins. Additionally, operations on images such as edge detection and color clustering have also been added. ...
    Downloads: 18 This Week
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  • 4
    Delta ML

    Delta ML

    Deep learning based natural language and speech processing platform

    DELTA is a deep learning-based end-to-end natural language and speech processing platform. DELTA aims to provide easy and fast experiences for using, deploying, and developing natural language processing and speech models for both academia and industry use cases. DELTA is mainly implemented using TensorFlow and Python 3. DELTA has been used for developing several state-of-the-art algorithms for publications and delivering real production to serve millions of users.
    Downloads: 0 This Week
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  • 5
    PyText

    PyText

    A natural language modeling framework based on PyTorch

    ...We use PyText at Facebook to iterate quickly on new modeling ideas and then seamlessly ship them at scale. Distributed-training support built on the new C10d backend in PyTorch 1.0. Mixed precision training support through APEX (trains faster with less GPU memory on NVIDIA Tensor Cores). Extensible components that allows easy creation of new models and tasks.
    Downloads: 0 This Week
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  • 6
    End-to-End Negotiator

    End-to-End Negotiator

    Deal or No Deal? End-to-End Learning for Negotiation Dialogues

    ...It enables agents to plan, reason, and communicate effectively to maximize outcomes in multi-turn negotiations over shared resources. The framework provides code for both supervised learning (training from human dialogue data) and reinforcement learning (via self-play and rollout-based planning). It introduces a hierarchical latent model, where high-level intents are first clustered and then translated into coherent language, improving dialogue diversity and goal consistency. The repository also includes the Negotiate dataset, comprising over 5,800 dialogues across 2,200 unique scenarios.
    Downloads: 1 This Week
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  • 7
    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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  • 8
    ChainerCV

    ChainerCV

    ChainerCV: a Library for Deep Learning in Computer Vision

    ChainerCV is a collection of tools to train and run neural networks for computer vision tasks using Chainer. In ChainerCV, we define the object detection task as a problem of, given an image, bounding box-based localization and categorization of objects. Bounding boxes in an image are represented as a two-dimensional array of shape (R,4), where R is the number of bounding boxes and the second axis corresponds to the coordinates of bounding boxes.
    Downloads: 0 This Week
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  • 9
    Easy-TensorFlow

    Easy-TensorFlow

    Simple and comprehensive tutorials in TensorFlow

    The goal of this repository is to provide comprehensive tutorials for TensorFlow while maintaining the simplicity of the code. Each tutorial includes a detailed explanation (written in .ipynb) format, as well as the source code (in .py format). There is a necessity to address the motivations for this project. TensorFlow is one of the deep learning frameworks available with the largest community. This repository is dedicated to suggesting a simple path to learn TensorFlow. In addition to the...
    Downloads: 0 This Week
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  • 10
    LearningToCompare_FSL

    LearningToCompare_FSL

    Learning to Compare: Relation Network for Few-Shot Learning

    LearningToCompare_FSL is a PyTorch implementation of the “Learning to Compare: Relation Network for Few-Shot Learning” paper, focusing on the few-shot learning experiments described in that work. The core idea implemented here is the relation network, which learns to compare pairs of feature embeddings and output relation scores that indicate whether two images belong to the same class, enabling classification from only a handful of labeled examples. The repository provides training and...
    Downloads: 0 This Week
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  • 11
    Deep Reinforcement Learning TensorFlow

    Deep Reinforcement Learning TensorFlow

    TensorFlow implementation of Deep Reinforcement Learning papers

    Deep Reinforcement Learning TensorFlow is a comprehensive TensorFlow codebase that implements several foundational deep reinforcement learning algorithms for educational and experimental use. The repository focuses on clarity and modularity so users can study how different RL approaches are built and compare their behavior across environments. It includes implementations of well-known algorithms such as Deep Q-Networks (DQN), policy gradients, and related variants, demonstrating how neural...
    Downloads: 0 This Week
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  • 12

    Face Recognition

    World's simplest facial recognition api for Python & the command line

    Face Recognition is the world's simplest face recognition library. It allows you to recognize and manipulate faces from Python or from the command line using dlib's (a C++ toolkit containing machine learning algorithms and tools) state-of-the-art face recognition built with deep learning. Face Recognition is highly accurate and is able to do a number of things. It can find faces in pictures, manipulate facial features in pictures, identify faces in pictures, and do face recognition on a...
    Downloads: 7 This Week
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