Showing 4715 open source projects for "machine"

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  • 1
    Kashgari

    Kashgari

    Kashgari is a production-level NLP Transfer learning framework

    Kashgari is a simple and powerful NLP Transfer learning framework, build a state-of-art model in 5 minutes for named entity recognition (NER), part-of-speech tagging (PoS), and text classification tasks.
    Downloads: 0 This Week
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  • 2
    masmt

    masmt

    A frame work for Multi agent system development

    MaSMT is a java based multi-agent system development framework, especially designed for development of English to Sinhala machine translation system. MaSMT also capable to develop any multi-agent based system through its architecture. Reference: B. Hettige, A. S. Karunananda, G. Rzevski, Multi-agent solution for managing complexity in English to Sinhala Machine Translation, International Journal of Design & Nature and Ecodynamics, Volume 11, Issue 2, 2016, 88 – 96. ...
    Downloads: 0 This Week
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  • 3
    Arraymancer

    Arraymancer

    A fast, ergonomic and portable tensor library in Nim

    Arraymancer is a tensor and deep learning library for the Nim programming language, designed for high-performance numerical computations and machine learning applications.
    Downloads: 0 This Week
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  • 4
    libpostal

    libpostal

    A C library for parsing/normalizing street addresses around the world

    ...Yet even the simplest addresses are packed with local conventions, abbreviations and context, making them difficult to index/query effectively with traditional full-text search engines. This library helps convert the free-form addresses that humans use into clean normalized forms suitable for machine comparison and full-text indexing. Though libpostal is not itself a full geocoder, it can be used as a preprocessing step to make any geocoding application smarter, and simpler.
    Downloads: 1 This Week
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  • 5
    Microsoft Bot Framework SDK

    Microsoft Bot Framework SDK

    Tool for building conversation applications

    Bot Framework provides the most comprehensive experience for building conversation applications. With the Bot Framework SDK, developers can build bots that converse free-form or with guided interactions including using simple text or rich cards that contain text, images, and action buttons. Developers can model and build sophisticated conversation using their favorite programming languages including C#, JS, Python and Java or using Bot Framework Composer, an open-source, visual authoring...
    Downloads: 0 This Week
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  • 6
    GoSpider

    GoSpider

    Gospider - Fast web spider written in Go

    ...Parse robots.txt. Generate and verify link from JavaScript files. Link Finder. Find AWS-S3 from response source. Find subdomains from the response source. Get URLs from Wayback Machine, Common Crawl, Virus Total, Alien Vault. Format output easy to Grep. Support Burp input. Crawl multiple sites in parallel.
    Downloads: 1 This Week
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  • 7
    Easy Agent Simulation

    Easy Agent Simulation

    Java-based agent simulation platform

    EAS is a Java-based simulation platform, developed as part of a research project at the Karlsruhe Institute of Technology. It comes with a broad range of pre-developed simulation scenarios, ranging from virtual agents acting in abstract environments to agents with a spatial representation in 2D or 3D. It is built upon a novel architecture using a separate "plugin layer" to communicate between the simulation engine and the simulated model. This allows to flexibly add or remove...
    Downloads: 0 This Week
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  • 8
    Hydra Booster

    Hydra Booster

    A DHT Indexer node & Peer Router

    ...Having more DHT nodes behind NATs makes DHT queries in general slower, as connecting in generally takes longer and sometimes doesn't even work (resulting in a timeout). The total number of heads a single Hydra can have depends on the resources of the machine it's running on. To get the desired number of heads you may need to run multiple Hydras on multiple machines.
    Downloads: 3 This Week
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  • 9
    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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  • 10
    FARM

    FARM

    Fast & easy transfer learning for NLP

    FARM makes Transfer Learning with BERT & Co simple, fast and enterprise-ready. It's built upon transformers and provides additional features to simplify the life of developers: Parallelized preprocessing, highly modular design, multi-task learning, experiment tracking, easy debugging and close integration with AWS SageMaker. With FARM you can build fast proofs-of-concept for tasks like text classification, NER or question answering and transfer them easily into production. Easy fine-tuning...
    Downloads: 1 This Week
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  • 11
    VPLE

    VPLE

    Vulnerable Pentesting Lab Environment

    VPLE (Linux) Vulnerable Pentesting Lab Environment VPLE is an Intentionally Vulnerable Linux Virtual Machine. This VM can be used to conduct security training, test security tools, and practice common penetration testing Labs. In VPLE bunch of labs are Available. NOTE:- "Only run in VMWare Pls Don’t run in VirtualBox" The default login and password is administrator: password. List Of All Labs in one VM:- 1. Web-DVWA 2. Mutillidae 3.
    Downloads: 10 This Week
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  • 12
    AliceMind

    AliceMind

    ALIbaba's Collection of Encoder-decoders from MinD

    This repository provides pre-trained encoder-decoder models and its related optimization techniques developed by Alibaba's MinD (Machine IntelligeNce of Damo) Lab. Pre-trained models for natural language understanding (NLU). We extend BERT to a new model, StructBERT, by incorporating language structures into pre-training. Specifically, we pre-train StructBERT with two auxiliary tasks to make the most of the sequential order of words and sentences, which leverage language structures at the word and sentence levels, respectively. ...
    Downloads: 1 This Week
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  • 13
    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. The template includes configuration files, scripts, and project structures that help teams build reproducible experiments and production-ready pipelines. ...
    Downloads: 0 This Week
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  • 14
    Minkowski Engine

    Minkowski Engine

    Auto-diff neural network library for high-dimensional sparse tensors

    The Minkowski Engine is an auto-differentiation library for sparse tensors. It supports all standard neural network layers such as convolution, pooling, unspooling, and broadcasting operations for sparse tensors. The Minkowski Engine supports various functions that can be built on a sparse tensor. We list a few popular network architectures and applications here. To run the examples, please install the package and run the command in the package root directory. Compressing a neural network to...
    Downloads: 2 This Week
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  • 15
    Machine Learning Beginner

    Machine Learning Beginner

    Machine Learning Beginner Public Account Works

    Machine Learning Beginner targets newcomers who are just getting started with machine learning and need a gentle, guided path. It introduces the core vocabulary and the mental map of supervised and unsupervised learning before moving into simple algorithms. The materials prioritize conceptual clarity, then progressively add code to solidify understanding.
    Downloads: 0 This Week
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  • 16
    neurojs

    neurojs

    A JavaScript deep learning and reinforcement learning library

    neurojs is a JavaScript framework designed to enable deep learning and reinforcement learning directly within web environments. The library provides a full machine learning framework implemented in JavaScript that can run inside browsers or Node.js environments. It focuses particularly on reinforcement learning algorithms, enabling developers to create intelligent agents that learn through interaction with simulated environments. The framework supports neural network architectures and reinforcement learning methods such as deep Q-networks and actor-critic algorithms. ...
    Downloads: 4 This Week
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  • 17
    TensorFlow.js models

    TensorFlow.js models

    Pretrained models for TensorFlow.js

    ...They can be used directly or used in a transfer learning setting with TensorFlow.js. To find out about APIs for models, look at the README in each of the respective directories. In general, we try to hide tensors so the API can be used by non-machine learning experts. New models should have a test NPM script. You can run the unit tests for any of the models by running "yarn test" inside a directory. Use off-the-shelf JavaScript models or convert Python TensorFlow models to run in the browser or under Node.js. Build and train models directly in JavaScript using flexible and intuitive APIs. ...
    Downloads: 1 This Week
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  • 18
    Machine-Learning-Notes

    Machine-Learning-Notes

    Zhou Zhihua's "Machine Learning" push notes

    The Machine-Learning-Notes repository contains detailed handwritten-style study notes based on the popular machine learning textbook by Zhou Zhihua. The project focuses on deriving formulas and explaining algorithms step by step so that learners can understand the mathematical foundations behind machine learning methods. The notes span sixteen chapters that cover a wide range of topics, including model evaluation, linear models, decision trees, neural networks, support vector machines, Bayesian classifiers, ensemble methods, clustering, dimensionality reduction, and reinforcement learning. ...
    Downloads: 1 This Week
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  • 19
    SRU

    SRU

    Training RNNs as Fast as CNNs

    Common recurrent neural architectures scale poorly due to the intrinsic difficulty in parallelizing their state computations. In this work, we propose the Simple Recurrent Unit (SRU), a light recurrent unit that balances model capacity and scalability. SRU is designed to provide expressive recurrence, enable highly parallelized implementation, and comes with careful initialization to facilitate the training of deep models. We demonstrate the effectiveness of SRU on multiple NLP tasks. SRU...
    Downloads: 1 This Week
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  • 20
    course-v3

    course-v3

    The 3rd edition of course.fast.ai

    course-v3 repository contains the complete learning materials for the third edition of the Practical Deep Learning for Coders course developed by the fast.ai research group. The repository includes Jupyter notebooks, lesson materials, datasets, and supporting documentation used in the course to teach modern deep learning techniques. The course emphasizes a top-down approach to learning artificial intelligence, where students begin by building practical models and later study the underlying...
    Downloads: 0 This Week
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  • 21
    Hands-on Unsupervised Learning

    Hands-on Unsupervised Learning

    Code for Hands-on Unsupervised Learning Using Python (O'Reilly Media)

    This repo contains the code for the O'Reilly Media, Inc. book "Hands-on Unsupervised Learning Using Python: How to Build Applied Machine Learning Solutions from Unlabeled Data" by Ankur A. Patel. Many industry experts consider unsupervised learning the next frontier in artificial intelligence, one that may hold the key to the holy grail in AI research, the so-called general artificial intelligence. Since the majority of the world's data is unlabeled, conventional supervised learning cannot be applied; this is where unsupervised learning comes in. ...
    Downloads: 0 This Week
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  • 22
    ml-design-patterns

    ml-design-patterns

    Source code accompanying O'Reilly book: Machine Learning Design

    The ml-design-patterns repository contains the source code and examples that accompany the book “Machine Learning Design Patterns,” providing practical implementations of reusable solutions for common challenges in machine learning systems. It organizes patterns into categories such as data representation, problem framing, and model training, helping practitioners understand how to structure ML pipelines effectively. The repository includes implementations of techniques like feature hashing, embeddings, feature crosses, and multimodal inputs, which are essential for handling diverse data types. ...
    Downloads: 0 This Week
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  • 23
    Opyrator

    Opyrator

    Turns your machine learning code into microservices with web API

    Instantly turn your Python functions into production-ready microservices. Deploy and access your services via HTTP API or interactive UI. Seamlessly export your services into portable, shareable, and executable files or Docker images. Opyrator builds on open standards - OpenAPI, JSON Schema, and Python type hints - and is powered by FastAPI, Streamlit, and Pydantic. It cuts out all the pain for productizing and sharing your Python code - or anything you can wrap into a single Python...
    Downloads: 0 This Week
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  • 24
    SimCSE

    SimCSE

    SimCSE: Simple Contrastive Learning of Sentence Embeddings

    SimCSE (Simple Contrastive Learning of Sentence Embeddings) is a machine learning framework for training sentence embeddings using contrastive learning. It improves representation learning for NLP tasks.
    Downloads: 0 This Week
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  • 25
    Arduino Simulator Drag & Draw MacOS

    Arduino Simulator Drag & Draw MacOS

    Simulate your IO with this Arduino Simulator

    ...It is also possible to load a background into the worksheet. You can also combine simulated inputs/outputs from the pc and real Arduino IO, now you have made a little HMI (Human Machine Interface). It's also possible to simulate through TCP WiFi-Ethernet connection. Free license key: 4C9G9-725IT-CYUV4-6KDBF-CPDEU More information: https://xevro.be/products/arduino-simulator-drag-draw-macos.html
    Downloads: 0 This Week
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