Showing 196 open source projects for "python basic project"

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  • 1
    TensorFlow Object Counting API

    TensorFlow Object Counting API

    The TensorFlow Object Counting API is an open source framework

    ...The API will be updated soon, the more talented and light-weight API will be available in this repo! Detailed API documentation and sample jupyter notebooks that explain basic usages of API will be added!
    Downloads: 0 This Week
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  • 2
    Knock Knock

    Knock Knock

    Get notified when your training ends

    ...These alerts can be delivered through several communication platforms such as email, Slack, Telegram, or other messaging services. The goal of the project is to allow developers to monitor experiments remotely without needing to stay connected to the training environment. By adding only a few lines of code, the library can wrap around a training function and report execution status.
    Downloads: 1 This Week
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  • 3
    Top deep learning Github repositories

    Top deep learning Github repositories

    Top 200 deep learning Github repositories sorted by stars

    Top-Deep-Learning is a curated repository that aggregates some of the most influential and widely used deep learning projects available on GitHub. Instead of providing its own machine learning models or frameworks, the project functions as an organized index that helps users discover high-quality deep learning repositories across different application domains. The repository categorizes projects related to neural networks, computer vision, natural language processing, reinforcement learning,...
    Downloads: 0 This Week
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  • 4
    Spinning Up in Deep RL

    Spinning Up in Deep RL

    Educational resource to help anyone learn deep reinforcement learning

    Welcome to Spinning Up in Deep RL! This is an educational resource produced by OpenAI that makes it easier to learn about deep reinforcement learning (deep RL). For the unfamiliar, reinforcement learning (RL) is a machine learning approach for teaching agents how to solve tasks by trial and error. Deep RL refers to the combination of RL with deep learning. At OpenAI, we believe that deep learning generally, and deep reinforcement learning specifically, will play central roles in the...
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  • 5
    MMSkeleton

    MMSkeleton

    A OpenMMLAB toolbox for human pose estimation, skeleton-based action

    MMSkeleton is an open-source toolbox for skeleton-based human understanding. It is a part of the open-mmlab project in the charge of Multimedia Laboratory, CUHK. MMSkeleton is developed on our research project ST-GCN. MMSkeleton provides a flexible framework for organizing codes and projects systematically, with the ability to extend to various tasks and scale up to complex deep models. MMSkeleton addresses to multiple tasks in human understanding. Build a custom skeleton-based dataset....
    Downloads: 0 This Week
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  • 6
    Image Super-Resolution (ISR)

    Image Super-Resolution (ISR)

    Super-scale your images and run experiments with Residual Dense

    The goal of this project is to upscale and improve the quality of low-resolution images. This project contains Keras implementations of different Residual Dense Networks for Single Image Super-Resolution (ISR) as well as scripts to train these networks using content and adversarial loss components. Docker scripts and Google Colab notebooks are available to carry training and prediction.
    Downloads: 3 This Week
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  • 7
    TensorFlow Machine Learning Cookbook

    TensorFlow Machine Learning Cookbook

    Code for Tensorflow Machine Learning Cookbook

    ...By combining theoretical explanations with executable code, the project helps developers understand how TensorFlow algorithms operate internally while also providing working examples that can be adapted for real projects.
    Downloads: 0 This Week
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  • 8
    Machine Learning with TensorFlow

    Machine Learning with TensorFlow

    Accompanying source code for Machine Learning with TensorFlow

    Machine Learning with TensorFlow is an open repository containing the source code and practical examples that accompany the book Machine Learning with TensorFlow. The project provides numerous code samples demonstrating how to build machine learning models using the TensorFlow framework. These examples illustrate core machine learning concepts such as regression, classification, clustering, and neural networks through practical implementations. The repository includes implementations of...
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  • 9
    Machine Learning From Scratch

    Machine Learning From Scratch

    Bare bones NumPy implementations of machine learning models

    ML-From-Scratch is an open-source machine learning project that demonstrates how to implement common machine learning algorithms using only basic Python and NumPy rather than relying on high-level frameworks. The goal of the project is to help learners understand how machine learning algorithms work internally by building them step by step from fundamental mathematical operations. The repository includes implementations of algorithms ranging from simple models such as linear regression and logistic regression to more complex techniques such as decision trees, support vector machines, clustering methods, and neural networks. ...
    Downloads: 1 This Week
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  • 10
    Image Quality Assessment

    Image Quality Assessment

    Convolutional Neural Networks to predict aesthetic quality of images

    Image Quality Assessment is an open-source deep learning project that implements neural models for predicting the aesthetic and technical quality of digital images. The repository provides an implementation inspired by the NIMA (Neural Image Assessment) research approach, which uses convolutional neural networks trained on human-annotated datasets to estimate image quality scores. The goal of the project is to automatically evaluate images based on perceived quality factors such as...
    Downloads: 0 This Week
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  • 11
    PyTorch Natural Language Processing

    PyTorch Natural Language Processing

    Basic Utilities for PyTorch Natural Language Processing (NLP)

    PyTorch-NLP is a library for Natural Language Processing (NLP) in Python. It’s built with the very latest research in mind, and was designed from day one to support rapid prototyping. PyTorch-NLP comes with pre-trained embeddings, samplers, dataset loaders, metrics, neural network modules and text encoders. It’s open-source software, released under the BSD3 license. With your batch in hand, you can use PyTorch to develop and train your model using gradient descent. For example, check out...
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  • 12
    Dive-into-DL-TensorFlow2.0

    Dive-into-DL-TensorFlow2.0

    Dive into Deep Learning

    This project changes the MXNet code implementation in the original book "Learning Deep Learning by Hand" to TensorFlow2 implementation. After consulting Mr. Li Mu by the tutor of archersama , the implementation of this project has been agreed by Mr. Li Mu. Original authors: Aston Zhang, Li Mu, Zachary C. Lipton, Alexander J. Smola and other community contributors. There are some differences between the Chinese and English versions of this book . This project mainly focuses on TensorFlow2...
    Downloads: 0 This Week
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  • 13
    Torchreid

    Torchreid

    Deep learning person re-identification in PyTorch

    Torchreid is a library for deep-learning person re-identification, written in PyTorch and developed for our ICCV’19 project, Omni-Scale Feature Learning for Person Re-Identification. In "deep-person-reid/scripts/", we provide a unified interface to train and test a model. See "scripts/main.py" and "scripts/default_config.py" for more details. The folder "configs/" contains some predefined configs which you can use as a starting point. The code will automatically (download and) load the...
    Downloads: 0 This Week
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  • 14
    ELI5

    ELI5

    A library for debugging/inspecting machine learning classifiers

    ELI5 is a Python library designed to help developers interpret, debug, and explain the predictions of machine learning models. The project focuses on improving model transparency by providing tools that visualize feature importance and prediction reasoning. It supports several popular machine learning frameworks including scikit-learn, XGBoost, LightGBM, CatBoost, and Keras.
    Downloads: 1 This Week
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  • 15
    AIAlpha

    AIAlpha

    Use unsupervised and supervised learning to predict stocks

    AIAlpha is a machine learning project focused on building predictive models for financial markets and algorithmic trading strategies. The repository explores how artificial intelligence techniques can analyze historical financial data and generate predictions about asset price movements. It provides a research-oriented environment where users can experiment with data processing pipelines, model training workflows, and quantitative trading strategies. The project typically involves collecting...
    Downloads: 0 This Week
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  • 16
    captcha_break

    captcha_break

    Identification codes

    This project will use Keras to build a deep convolutional neural network to identify the captcha verification code. It is recommended to use a graphics card to run the project. The following visualization codes are jupyter notebookall done in . If you want to write a python script, you can run it normally with a little modification. Of course, you can also remove these visualization codes. captcha is a library written in python to generate verification codes. ...
    Downloads: 1 This Week
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  • 17
    SSD

    SSD

    A PyTorch Implementation of Single Shot MultiBox Detector

    SSD is a PyTorch implementation of the Single Shot MultiBox Detector, a well-known object detection architecture introduced in the original SSD paper. It is built to help users train, evaluate, and experiment with object detection models using PyTorch rather than the original Caffe implementation. The repository includes the major components needed for an object detection workflow, including training scripts, evaluation scripts, demos, and utility modules. It supports commonly used benchmark...
    Downloads: 0 This Week
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  • 18
    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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  • 19
    LUMINOTH

    LUMINOTH

    Deep Learning toolkit for Computer Vision

    ...The toolkit provides command-line utilities for dataset management, training, and inference, making it easier to integrate into research workflows and production systems. Although the project is no longer actively maintained, it remains a useful educational and experimental platform for studying object detection pipelines and deep learning workflows.
    Downloads: 0 This Week
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  • 20
    BossSensor

    BossSensor

    Hide screen when boss is approaching

    ...The software relies on libraries such as OpenCV, TensorFlow, and Python-based machine learning tools to perform face detection and classification. Training the system requires a dataset of labeled images representing the boss and other people so that the model can learn to differentiate between them.
    Downloads: 0 This Week
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  • 21
    Dynamic Routing Between Capsules

    Dynamic Routing Between Capsules

    A PyTorch implementation of the NIPS 2017 paper

    Dynamic Routing Between Capsules is a PyTorch implementation of the Capsule Network architecture originally proposed to address limitations in traditional convolutional neural networks. Capsule networks aim to improve how neural models represent spatial hierarchies and relationships between objects within images. Instead of scalar neuron activations, capsules output vectors that encode both the presence of features and their spatial properties such as orientation or pose. The repository...
    Downloads: 0 This Week
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  • 22
    Lihang

    Lihang

    Statistical learning methods (2nd edition) [Li Hang]

    Lihang is an open-source repository that provides educational notes, mathematical derivations, and code implementations based on the book Statistical Learning Methods by Li Hang. The repository aims to help readers understand the theoretical foundations of machine learning algorithms through practical implementations and detailed explanations. It includes notebooks and scripts that demonstrate how key algorithms such as perceptrons, decision trees, logistic regression, support vector...
    Downloads: 0 This Week
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  • 23
    The GAN Zoo

    The GAN Zoo

    A list of all named GANs

    The GAN Zoo is an open-source repository that compiles a comprehensive list of Generative Adversarial Network models published in research literature. The project began as a community effort to track the rapidly growing number of GAN architectures appearing in machine learning papers. Because new GAN models are frequently introduced in research publications, the repository serves as a convenient catalog that organizes them in one location. The list includes references to many GAN variants...
    Downloads: 0 This Week
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  • 24
    Generative Models

    Generative Models

    Collection of generative models, e.g. GAN, VAE in Pytorch

    This project is a comprehensive open-source collection of implementations of various generative machine learning models designed to help researchers and developers experiment with deep generative techniques. The repository contains practical implementations of well-known architectures such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), Restricted Boltzmann Machines, and Helmholtz Machines, implemented primarily using modern deep learning frameworks like PyTorch...
    Downloads: 1 This Week
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  • 25
    SSD Keras

    SSD Keras

    A Keras port of single shot MultiBox detector

    This is a Keras port of the SSD model architecture introduced by Wei Liu et al. in the paper SSD: Single Shot MultiBox Detector. Ports of the trained weights of all the original models are provided below. This implementation is accurate, meaning that both the ported weights and models trained from scratch produce the same mAP values as the respective models of the original Caffe implementation. The main goal of this project is to create an SSD implementation that is well documented for those...
    Downloads: 0 This Week
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