143 projects for "python project" with 2 filters applied:

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  • 1
    Machine Learning & Deep Learning

    Machine Learning & Deep Learning

    machine learning and deep learning tutorials, articles

    Machine Learning & Deep Learning Tutorials is an open-source repository that provides practical tutorials demonstrating how to implement machine learning and deep learning models using popular frameworks such as TensorFlow and PyTorch. The project focuses on helping learners understand machine learning through hands-on coding examples rather than purely theoretical explanations. Each tutorial walks through the process of building and training models for tasks such as image classification,...
    Downloads: 2 This Week
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  • 2
    SparrowRecSys

    SparrowRecSys

    A Deep Learning Recommender System

    SparrowRecSys is an open-source deep learning recommendation system framework designed to demonstrate the architecture and implementation of modern industrial-scale recommender systems. The project integrates multiple machine learning models and data processing pipelines to simulate how real-world recommendation platforms operate. It includes components for offline data processing, feature engineering, model training, real-time data updates, and online recommendation services. SparrowRecSys...
    Downloads: 0 This Week
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  • 3
    Sklearn TensorFlow

    Sklearn TensorFlow

    Sklearn and TensorFlow: A Practical Guide to Machine Learning

    ...It focuses on teaching core machine learning concepts using Python while demonstrating practical workflows with popular libraries like Scikit-Learn and TensorFlow. The material covers topics ranging from basic machine learning theory to deep learning techniques and model evaluation, enabling learners to build and experiment with models step by step.
    Downloads: 0 This Week
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  • 4
    YOLOv4-large

    YOLOv4-large

    Scaled-YOLOv4: Scaling Cross Stage Partial Network

    YOLOv4-large is an open-source implementation of the Scaled-YOLOv4 object detection architecture, designed to improve both the accuracy and scalability of real-time computer vision models. The project provides a PyTorch implementation of the Scaled-YOLOv4 framework, which extends the original YOLOv4 architecture using Cross Stage Partial (CSP) networks and new scaling techniques. Unlike earlier object detection systems that only scale depth or width, this architecture scales multiple aspects...
    Downloads: 0 This Week
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  • 5
    tensorflow_template_application

    tensorflow_template_application

    TensorFlow template application for deep learning

    tensorflow_template_application is a template project that demonstrates how to structure scalable applications built with TensorFlow. The repository provides a standardized architecture that helps developers organize machine learning code into clear components such as data processing, model training, evaluation, and deployment. Instead of focusing on a specific algorithm, the project emphasizes software engineering practices that make machine learning systems easier to maintain and extend....
    Downloads: 0 This Week
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  • 6
    MachineLearningStocks

    MachineLearningStocks

    Using python and scikit-learn to make stock predictions

    MachineLearningStocks is a Python-based template project that demonstrates how machine learning can be applied to predicting stock market performance. The project provides a structured workflow that collects financial data, processes features, trains predictive models, and evaluates trading strategies. Using libraries such as pandas and scikit-learn, the repository shows how historical financial indicators can be transformed into machine learning features.
    Downloads: 0 This Week
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  • 7
    Swift for TensorFlow

    Swift for TensorFlow

    Swift for TensorFlow

    Swift for TensorFlow repository contains the open-source implementation of Swift for TensorFlow, a project that integrates machine learning capabilities directly into the Swift programming language. The initiative aims to provide a new programming model for developing machine learning systems by combining the power of TensorFlow with language-level features such as automatic differentiation and strong type systems. By embedding machine learning functionality into the Swift compiler and...
    Downloads: 0 This Week
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  • 8
    ALAE

    ALAE

    Adversarial Latent Autoencoders

    ALAE (Adversarial Latent Autoencoders) is a deep learning research implementation that combines autoencoders with generative adversarial networks to produce high-quality image synthesis models. The project implements the architecture introduced in the CVPR research paper on Adversarial Latent Autoencoders, which focuses on improving generative modeling by learning latent representations aligned with adversarial training objectives. Unlike traditional GANs that directly generate images from...
    Downloads: 0 This Week
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  • 9
    surpriver

    surpriver

    Find big moving stocks before they move using machine learning

    surpriver is a machine learning project designed to identify unusual stock market activity that may precede large price movements. The system analyzes historical stock price and volume data to detect anomalies that could indicate potential trading opportunities. By applying machine learning techniques to market indicators, the tool attempts to identify patterns in trading behavior that deviate significantly from normal market activity. These anomalies are interpreted as signals that a stock...
    Downloads: 0 This Week
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  • 10
    NLP-Models-Tensorflow

    NLP-Models-Tensorflow

    Gathers machine learning and Tensorflow deep learning models for NLP

    NLP-Models-Tensorflow is a collection of natural language processing model implementations built using the TensorFlow deep learning framework. The repository provides numerous examples of neural network architectures used in modern NLP research and applications, including text classification, language modeling, machine translation, and sentiment analysis. Each model implementation is designed to illustrate how common NLP architectures operate, such as recurrent neural networks, convolutional...
    Downloads: 0 This Week
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  • 11
    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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  • 12
    python-is-cool

    python-is-cool

    Cool Python features for machine learning

    python-is-cool is an educational repository created by AI researcher Chip Huyen that explores lesser-known features and powerful capabilities of the Python programming language. The project serves as a curated guide to Python techniques that many developers may overlook or hesitate to use due to unfamiliarity. It demonstrates practical language features, idiomatic programming patterns, and useful tricks that can make Python code more expressive, efficient, and elegant. ...
    Downloads: 0 This Week
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  • 13
    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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  • 14
    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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  • 15
    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...
    Downloads: 0 This Week
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  • 16
    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: 1 This Week
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  • 17
    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: 0 This Week
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  • 18
    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: 0 This Week
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  • 19
    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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  • 20
    Girls-In-AI

    Girls-In-AI

    Free learning code series: Xiaobai's introduction to Python

    ...One of the primary goals of the project is to support inclusivity in technology by encouraging more women and newcomers to explore programming and AI development.
    Downloads: 1 This Week
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  • 21
    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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  • 22
    Python Data Science Tutorials

    Python Data Science Tutorials

    Common data analysis and machine learning tasks using python

    ...Additional material addresses text mining, sentiment analysis, serialization with pickle, AutoML, regular expressions, and web scraping. The repository is organized by topic so learners can use it as a study roadmap or troubleshooting index. Many links document the earlier Python data science ecosystem, making the project especially valuable as a broad historical resource collection.
    Downloads: 0 This Week
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  • 23
    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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  • 24
    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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  • 25
    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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