Showing 531 open source projects for "machine"

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  • 1
    TensorFlow Model Optimization Toolkit

    TensorFlow Model Optimization Toolkit

    A toolkit to optimize ML models for deployment for Keras & TensorFlow

    The TensorFlow Model Optimization Toolkit is a suite of tools for optimizing ML models for deployment and execution. Among many uses, the toolkit supports techniques used to reduce latency and inference costs for cloud and edge devices (e.g. mobile, IoT). Deploy models to edge devices with restrictions on processing, memory, power consumption, network usage, and model storage space. Enable execution on and optimize for existing hardware or new special purpose accelerators. Choose the model...
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  • 2
    Robyn

    Robyn

    Experimental, AI/ML-powered and open sourced Marketing Mix Modeling

    Robyn is an open-source, AI/ML-powered Marketing Mix Modeling (MMM) toolkit developed by Meta Marketing Science under the “facebookexperimental” GitHub umbrella. Its goal is to democratize rigorous MMM: what traditionally required expert statisticians and expensive consulting becomes accessible to any company with data. Robyn takes in historical data (spends on different marketing channels, conversions, or revenue, and optional context or organic-media variables) and uses a combination of...
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  • 3
    Lightweight' GAN

    Lightweight' GAN

    Implementation of 'lightweight' GAN, proposed in ICLR 2021

    Implementation of 'lightweight' GAN proposed in ICLR 2021, in Pytorch. The main contribution of the paper is a skip-layer excitation in the generator, paired with autoencoding self-supervised learning in the discriminator. Quoting the one-line summary "converge on single gpu with few hours' training, on 1024 resolution sub-hundred images". Augmentation is essential for Lightweight GAN to work effectively in a low data setting. You can test and see how your images will be augmented before...
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  • 4
    tf2onnx

    tf2onnx

    Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX

    tf2onnx converts TensorFlow (tf-1.x or tf-2.x), keras, tensorflow.js and tflite models to ONNX via command line or python API. Note: tensorflow.js support was just added. While we tested it with many tfjs models from tfhub, it should be considered experimental. TensorFlow has many more ops than ONNX and occasionally mapping a model to ONNX creates issues. tf2onnx will use the ONNX version installed on your system and installs the latest ONNX version if none is found. We support and test ONNX...
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  • 5
    Sonnet

    Sonnet

    TensorFlow-based neural network library

    Sonnet is a neural network library built on top of TensorFlow designed to provide simple, composable abstractions for machine learning research. Sonnet can be used to build neural networks for various purposes, including different types of learning. Sonnet’s programming model revolves around a single concept: modules. These modules can hold references to parameters, other modules and methods that apply some function on the user input. There are a number of predefined modules that already ship with Sonnet, making it quite powerful and yet simple at the same time. ...
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  • 6
    PromptTools

    PromptTools

    Open-source tools for prompt testing and experimentation

    Welcome to prompttools created by Hegel AI! This repo offers a set of open-source, self-hostable tools for experimenting with, testing, and evaluating LLMs, vector databases, and prompts. The core idea is to enable developers to evaluate using familiar interfaces like code, notebooks, and a local playground.
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  • 7
    SSD in PyTorch 1.0

    SSD in PyTorch 1.0

    High quality, fast, modular reference implementation of SSD in PyTorch

    This repository implements SSD (Single Shot MultiBox Detector). The implementation is heavily influenced by the projects ssd.pytorch, pytorch-ssd and maskrcnn-benchmark. This repository aims to be the code base for research based on SSD. Multi-GPU training and inference: We use DistributedDataParallel, you can train or test with arbitrary GPU(s), the training schema will change accordingly. Add your own modules without pain. We abstract backbone, Detector, BoxHead, BoxPredictor, etc. You can...
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  • 8
    BackgroundMattingV2

    BackgroundMattingV2

    Real-Time High-Resolution Background Matting

    Official repository for the paper Real-Time High-Resolution Background Matting. Our model requires capturing an additional background image and produces state-of-the-art matting results at 4K 30fps and HD 60fps on an Nvidia RTX 2080 TI GPU.
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  • 9
    MMDeploy

    MMDeploy

    OpenMMLab Model Deployment Framework

    MMDeploy is an open-source deep learning model deployment toolset. It is a part of the OpenMMLab project. Models can be exported and run in several backends, and more will be compatible. All kinds of modules in the SDK can be extended, such as Transform for image processing, Net for Neural Network inference, Module for postprocessing and so on. Install and build your target backend. ONNX Runtime is a cross-platform inference and training accelerator compatible with many popular ML/DNN...
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  • 10
    MMEditing

    MMEditing

    MMEditing is a low-level vision toolbox based on PyTorch

    MMEditing is an open-source toolbox for low-level vision. It supports various tasks. MMEditing is a low-level vision toolbox based on PyTorch, supporting super-resolution, inpainting, matting, video interpolation, etc. We decompose the editing framework into different components and one can easily construct a customized editor framework by combining different modules. The toolbox directly supports popular and contemporary inpainting, matting, super-resolution and generation tasks. The...
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  • 11
    CLIP-as-service

    CLIP-as-service

    Embed images and sentences into fixed-length vectors

    CLIP-as-service is a low-latency high-scalability service for embedding images and text. It can be easily integrated as a microservice into neural search solutions. Serve CLIP models with TensorRT, ONNX runtime and PyTorch w/o JIT with 800QPS[*]. Non-blocking duplex streaming on requests and responses, designed for large data and long-running tasks. Horizontally scale up and down multiple CLIP models on single GPU, with automatic load balancing. Easy-to-use. No learning curve, minimalist...
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  • 12
    AStro inFER - a rule miner and executer
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  • 13
    Uranie

    Uranie

    Uranie is CEA's uncertainty analysis platform, based on ROOT

    Uranie is a sensitivity and uncertainty analysis plateform based on the ROOT framework (http://root.cern.ch) . It is developed at CEA, the French Atomic Energy Commission (http://www.cea.fr). It provides various tools for: - data analysis - sampling - statistical modeling - optimisation - sensitivity analysis - uncertainty analysis - running code on high performance computers - etc. Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. Is is...
    Downloads: 11 This Week
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  • 14
    Ubix Linux

    Ubix Linux

    The Pocket Datalab

    Ubix stands for Universal Business Intelligence Computing System. Ubix Linux is an open-source, Debian-based Linux distribution geared towards data acquisition, transformation, analysis and presentation. Ubix Linux purpose is to offer a tiny but versatile datalab. Ubix Linux is easily accessible, resource-efficient and completely portable on a simple USB key. Ubix Linux is a perfect toolset for learning data analysis and artificial intelligence basics on small to medium...
    Downloads: 7 This Week
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  • 15

    Taylorplot_Neptune

    Creation of a Taylorplot for several machine learning models

    Here we present the lines of code for creating a taylor plot with python to display several machine learning models. We show the solution for displaying 10 models, but the list and number can be changed simply by modifying the sample list.
    Downloads: 0 This Week
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  • 16
    Datapipe

    Datapipe

    Real-time, incremental ETL library for ML with record-level depend

    Datapipe is a real-time, incremental ETL library for Python with record-level dependency tracking. Datapipe is designed to streamline the creation of data processing pipelines. It excels in scenarios where data is continuously changing, requiring pipelines to adapt and process only the modified data efficiently. This library tracks dependencies for each record in the pipeline, ensuring minimal and efficient data processing.
    Downloads: 1 This Week
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  • 17
    Conscious Artificial Intelligence

    Conscious Artificial Intelligence

    It's possible for machines to become self-aware.

    This project is a quest for conscious artificial intelligence. A number of prototypes will be developed as the project progresses. This project has 2 subprojects: Object Pascal based CAI NEURAL API - https://github.com/joaopauloschuler/neural-api Python based K-CAI NEURAL API - https://github.com/joaopauloschuler/k-neural-api A video from the first prototype has been made: http://www.youtube.com/watch?v=qH-IQgYy9zg Above video shows a popperian agent collecting mining ore from 3...
    Downloads: 4 This Week
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  • 18
    PoseidonQ  - AI/ML Based QSAR Modeling

    PoseidonQ - AI/ML Based QSAR Modeling

    ML based QSAR Modelling And Translation of Model to Deployable WebApps

    - This Software was made with an intention to make QSAR building more efficient and reproducible. - Published in ACS, Journal of Chemical Information and Modeling . Link : https://pubs.acs.org/doi/10.1021/acs.jcim.4c02372 - Simple to use and no compromise on essential features necessary to make reliable QSAR models. - From Generating Reliable ML Based QSAR Models to Developing Your Own QSAR WebApp. For any feedback or queries, contact kabeermuzammil614@gmail.com - Available on Windows...
    Downloads: 5 This Week
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  • 19
    SMILI

    SMILI

    Scientific Visualisation Made Easy

    The Simple Medical Imaging Library Interface (SMILI), pronounced 'smilie', is an open-source, light-weight and easy-to-use medical imaging viewer and library for all major operating systems. The main sMILX application features for viewing n-D images, vector images, DICOMs, anonymizing, shape analysis and models/surfaces with easy drag and drop functions. It also features a number of standard processing algorithms for smoothing, thresholding, masking etc. images and models, both with...
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    Downloads: 5 This Week
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  • 20
    GNNPCSAFT

    GNNPCSAFT

    Smart Thermodynamic Modeling with Graph Neural Networks

    The GNNPCSAFT app is an implementation of our project that focuses on using Graph Neural Networks (GNN) to estimate the pure-component parameters of the Equation of State PC-SAFT. We developed this app so the scientific community can access the model's results easily. In this app, the estimated pure-component parameters can be used to calculate thermodynamic properties and compare them with experimental data from the ThermoML Archive. To install the GNNPCSAFT app, download the...
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  • 21
    TensorFlow Addons

    TensorFlow Addons

    Useful extra functionality for TensorFlow 2.x maintained by SIG-addons

    TensorFlow Addons is a repository of contributions that conform to well-established API patterns but implement new functionality not available in core TensorFlow. TensorFlow natively supports a large number of operators, layers, metrics, losses, and optimizers. However, in a fast-moving field like ML, there are many interesting new developments that cannot be integrated into core TensorFlow (because their broad applicability is not yet clear, or it is mostly used by a smaller subset of the...
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  • 22
    GNNPCSAFT Web App

    GNNPCSAFT Web App

    Smart Thermodynamic Modeling with Graph Neural Networks

    The GNNPCSAFT Web App is an implementation of our project that focuses on using Graph Neural Networks (GNN) to estimate the pure-component parameters of the Equation of State PC-SAFT. We developed this app so the scientific community can access the model's results easily. In this app, the estimated pure-component parameters can be used to calculate thermodynamic properties and compare them with experimental data from the ThermoML Archive. More info on github repository.
    Downloads: 0 This Week
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  • 23
    Zylthra

    Zylthra

    Zylthra: A PyQt6 app to generate synthetic datasets with DataLLM.

    Welcome to Zylthra, a powerful Python-based desktop application built with PyQt6, designed to generate synthetic datasets using the DataLLM API from data.mostly.ai. This tool allows users to create custom datasets by defining columns, configuring generation parameters, and saving setups for reuse, all within a sleek, dark-themed interface.
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  • 24
    SageMaker Inference Toolkit

    SageMaker Inference Toolkit

    Serve machine learning models within a Docker container

    Serve machine learning models within a Docker container using Amazon SageMaker. Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. Once you have a trained model, you can include it in a Docker container that runs your inference code.
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  • 25
    FEDML Open Source

    FEDML Open Source

    The unified and scalable ML library for large-scale training

    A Unified and Scalable Machine Learning Library for Running Training and Deployment Anywhere at Any Scale. TensorOpera AI is the next-gen cloud service for LLMs & Generative AI. It helps developers to launch complex model training, deployment, and federated learning anywhere on decentralized GPUs, multi-clouds, edge servers, and smartphones, easily, economically, and securely.
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