Showing 1274 open source projects for "machine learning python"

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  • 1
    Hugging Face Transformer

    Hugging Face Transformer

    CPU/GPU inference server for Hugging Face transformer models

    Optimize and deploy in production Hugging Face Transformer models in a single command line. At Lefebvre Dalloz we run in-production semantic search engines in the legal domain, in the non-marketing language it's a re-ranker, and we based ours on Transformer. In that setup, latency is key to providing a good user experience, and relevancy inference is done online for hundreds of snippets per user query. Most tutorials on Transformer deployment in production are built over Pytorch and FastAPI....
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  • 2
    Awesome Decision Tree Papers

    Awesome Decision Tree Papers

    A collection of research papers on decision, classification, etc.

    A collection of research papers on decision, classification and regression trees with implementations.
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  • 3
    AI Platform Training and Prediction
    AI Platform Training and Prediction is a collection of machine learning example projects that demonstrate how to train, deploy, and serve models using Google Cloud AI Platform and related services. It includes a wide variety of implementations across frameworks such as TensorFlow, PyTorch, scikit-learn, and XGBoost, allowing developers to explore different approaches to building ML solutions.
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  • 4
    Face Mask Detection

    Face Mask Detection

    Face Mask Detection system based on computer vision and deep learning

    Face Mask Detection system based on computer vision and deep learning using OpenCV and Tensorflow/Keras. Face Mask Detection System built with OpenCV, Keras/TensorFlow using Deep Learning and Computer Vision concepts in order to detect face masks in static images as well as in real-time video streams. Amid the ongoing COVID-19 pandemic, there are no efficient face mask detection applications which are now in high demand for transportation means, densely populated areas, residential...
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  • 5
    Graph4NLP

    Graph4NLP

    Graph4nlp is the library for the easy use of Graph Neural Networks

    Graph4NLP is an easy-to-use library for R&D at the intersection of Deep Learning on Graphs and Natural Language Processing (i.e., DLG4NLP). It provides both full implementations of state-of-the-art models for data scientists and also flexible interfaces to build customized models for researchers and developers with whole-pipeline support. Built upon highly-optimized runtime libraries including DGL , Graph4NLP has both high running efficiency and great extensibility. The architecture of...
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  • 6
    igel

    igel

    Machine learning tool that allows you to train and test models

    A delightful machine learning tool that allows you to train/fit, test, and use models without writing code. The goal of the project is to provide machine learning for everyone, both technical and non-technical users. I sometimes needed a tool sometimes, which I could use to fast create a machine learning prototype. Whether to build some proof of concept, create a fast draft model to prove a point or use auto ML.
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  • 7
    MACE

    MACE

    Deep learning inference framework optimized for mobile platforms

    Mobile AI Compute Engine (or MACE for short) is a deep learning inference framework optimized for mobile heterogeneous computing on Android, iOS, Linux and Windows devices. Runtime is optimized with NEON, OpenCL and Hexagon, and Winograd algorithm is introduced to speed up convolution operations. The initialization is also optimized to be faster. Chip-dependent power options like big.LITTLE scheduling, Adreno GPU hints are included as advanced APIs. UI responsiveness guarantee is sometimes...
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  • 8
    Machine-Learning

    Machine-Learning

    kNN, decision tree, Bayesian, logistic regression, SVM

    Machine-Learning is a repository focused on practical machine learning implementations in Python, covering classic algorithms like k-Nearest Neighbors, decision trees, naive Bayes, logistic regression, support vector machines, linear and tree-based regressions, and likely corresponding code examples and documentation. It targets learners or practitioners who want to understand and implement ML algorithms from scratch or via standard libraries, gaining hands-on experience rather than relying solely on black-box frameworks. ...
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  • 9
    scikit-learn tips

    scikit-learn tips

    50 scikit-learn tips

    scikit-learn-tips is an educational repository that collects practical advice and best practices for using the scikit-learn machine learning library effectively. The project consists of short explanations and examples that highlight common patterns, pitfalls, and techniques used when building machine learning workflows in Python. Each tip typically demonstrates how specific components of scikit-learn, such as pipelines, preprocessing utilities, or model evaluation tools, should be applied in real projects. ...
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  • 10
    Reformer PyTorch

    Reformer PyTorch

    Reformer, the efficient Transformer, in Pytorch

    This is a Pytorch implementation of Reformer. It includes LSH attention, reversible network, and chunking. It has been validated with an auto-regressive task (enwik8).
    Downloads: 1 This Week
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  • 11
    Teachable Machine

    Teachable Machine

    Explore how machine learning works, live in the browser

    Teachable Machine is the open-source implementation of an experimental machine learning tool created by Google Creative Lab that allows users to train simple machine learning models directly in a web browser. The project demonstrates how neural networks can be trained interactively using images captured from a webcam or other inputs without requiring programming knowledge.
    Downloads: 13 This Week
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  • 12
    Awesome Explainable Graph Reasoning

    Awesome Explainable Graph Reasoning

    A collection of research papers and software related to explainability

    A collection of research papers and software related to explainability in graph machine learning. Deep learning methods are achieving ever-increasing performance on many artificial intelligence tasks. A major limitation of deep models is that they are not amenable to interpretability. This limitation can be circumvented by developing post hoc techniques to explain the predictions, giving rise to the area of explainability.
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  • 13
    Trax

    Trax

    Deep learning with clear code and speed

    ...Trax includes basic models (like ResNet, LSTM, Transformer) and RL algorithms (like REINFORCE, A2C, PPO). It is also actively used for research and includes new models like the Reformer and new RL algorithms like AWR. Trax has bindings to a large number of deep learning datasets, including Tensor2Tensor and TensorFlow datasets. You can use Trax either as a library from your own python scripts and notebooks or as a binary from the shell, which can be more convenient for training large models. It runs without any changes on CPUs, GPUs and TPUs.
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  • 14
    ChoiceMaker
    Record matching software
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  • 15
    Scikit-Optimize

    Scikit-Optimize

    Sequential model-based optimization with a `scipy.optimize` interface

    Scikit-Optimize, or skopt, is a simple and efficient library to minimize (very) expensive and noisy black-box functions. It implements several methods for sequential model-based optimization. skopt aims to be accessible and easy to use in many contexts. The library is built on top of NumPy, SciPy and Scikit-Learn.
    Downloads: 2 This Week
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  • 16
    hora

    hora

    Efficient approximate nearest neighbor search algorithm collections

    hora is an open-source high-performance vector similarity search library designed for large-scale machine learning and information retrieval systems. The project focuses on approximate nearest neighbor search, a fundamental technique used in modern AI applications such as recommendation systems, image search, and semantic search engines. Hora implements multiple efficient indexing algorithms that allow systems to rapidly search through high-dimensional vectors produced by machine learning models. ...
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  • 17
    TorchGAN

    TorchGAN

    Research Framework for easy and efficient training of GANs

    The torchgan package consists of various generative adversarial networks and utilities that have been found useful in training them. This package provides an easy-to-use API which can be used to train popular GANs as well as develop newer variants. The core idea behind this project is to facilitate easy and rapid generative adversarial model research. TorchGAN is a Pytorch-based framework for designing and developing Generative Adversarial Networks. This framework has been designed to...
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  • 18
    TensorRT Pro

    TensorRT Pro

    C++ library based on tensorrt integration

    High-level interface for C++/Python. Simplify the implementation of the custom plugin. And serialization and deserialization have been encapsulated for easier usage. Simplify the compilation of fp32, fp16 and int8 for facilitating the deployment with C++/Python in server or embedded device. Models ready for use also with examples are RetinaFace, Scrfd, YoloV5, YoloX, Arcface, AlphaPose, CenterNet and DeepSORT(C++).
    Downloads: 0 This Week
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  • 19
    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. ...
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  • 20
    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.
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  • 21
    AI-for-Security-Learning

    AI-for-Security-Learning

    AI-based security algorithms, and security data analysis

    AI-for-Security-Learning is an educational repository that explores the intersection of artificial intelligence and cybersecurity. The project compiles learning resources, examples, and experimental tools that demonstrate how machine learning techniques can be applied to security-related problems. Topics addressed in the repository include malware detection, anomaly detection, threat classification, and intrusion detection systems.
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  • 22
    Machine Learning Collection

    Machine Learning Collection

    A resource for learning about Machine learning & Deep Learning

    A resource for learning about Machine learning & Deep Learning. In this repository, you will find tutorials and projects related to Machine Learning. I try to make the code as clear as possible, and the goal is be to used as a learning resource and a way to look up problems to solve specific problems. For most, I have also done video explanations on YouTube if you want a walkthrough for the code.
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  • 23
    MTBook

    MTBook

    Machine Translation: Foundations and Models

    This is a tutorial, the purpose is to introduce the basic knowledge and modeling methods of machine translation systematically, and on this basis, discuss some cutting-edge technologies of machine translation (formerly known as "Machine Translation: Statistical Modeling and Deep Learning") method"). Its content is compiled into a book, which can be used for the study of senior undergraduates and graduate students in computer and artificial intelligence related majors, and can also be used as reference material for researchers related to natural language processing, especially machine translation. ...
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  • 24
    Perceptual Similarity Metric and Dataset

    Perceptual Similarity Metric and Dataset

    LPIPS metric. pip install lpips

    While it is nearly effortless for humans to quickly assess the perceptual similarity between two images, the underlying processes are thought to be quite complex. Despite this, the most widely used perceptual metrics today, such as PSNR and SSIM, are simple, shallow functions, and fail to account for many nuances of human perception. Recently, the deep learning community has found that features of the VGG network trained on ImageNet classification has been remarkably useful as a training...
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  • 25
    Tez

    Tez

    Tez is a super-simple and lightweight Trainer for PyTorch

    Tez is a super-simple and lightweight Trainer for PyTorch. It also comes with many utils that you can use to tackle over 90% of deep learning projects in PyTorch. tez (तेज़ / تیز) means sharp, fast & active. This is a simple, to-the-point, library to make your PyTorch training easy. This library is in early-stage currently! So, there might be breaking changes. Currently, tez supports cpu, single gpu and multi-gpu & tpu training. More coming soon! Using tez is super-easy. We don't want you to...
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