Showing 1058 open source projects for "python data analysis"

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  • Transforming NetOps Through No-Code Network Automation - NetBrain Icon
    Transforming NetOps Through No-Code Network Automation - NetBrain

    For anyone searching for a complete no-code automation platform for hybrid network observability and AIOps

    NetBrain, founded in 2004, provides a powerful no-code automation platform for hybrid network observability, allowing organizations to enhance their operational efficiency through automated workflows. The platform applies automation across three key workflows: troubleshooting, change management, and assessment.
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  • Office Ally: Healthcare Software for Your Medical Practice Icon
    Office Ally: Healthcare Software for Your Medical Practice

    We support healthcare organizations of all sizes with easy-to-use, affordable software solutions.

    Service Center by Office Ally is a trusted revenue cycle management platform used by over 65,000 healthcare organizations processing more than 350 million claims annually. With it, providers can verify patient eligibility and benefits, upload and submit claims, correct rejected claims, check claim status, and obtain remits. With multiple claim types and submission options, providers can easily submit claims to any payer from any practice management system. Transactions are secure, ensuring the confidentiality of sensitive patient information. With no needed implementation, providers can quickly and effortlessly streamline their billing processes, increase their financial performance, simplify medical billing, and reduce claim rejections for faster reimbursements.
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  • 1
    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. A container provides an effectively isolated environment, ensuring a consistent runtime regardless of where the...
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  • 2
    Chinese Llama 2 7B

    Chinese Llama 2 7B

    The first Chinese LLaMA2 model in the open source community

    Chinese Llama 2 7B is an open-source large language model adapted from the LLaMA-2 architecture and optimized for Chinese and bilingual Chinese-English applications. The project provides a version of LLaMA-2 that has been further trained on Chinese data so it can better understand and generate text in Chinese while maintaining compatibility with the original model ecosystem. In addition to the model weights, the repository also includes supervised fine-tuning datasets and training resources...
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  • 3
    Asteroid

    Asteroid

    The PyTorch-based audio source separation toolkit for researchers

    The PyTorch-based audio source separation toolkit for researchers. Pytorch-based audio source separation toolkit that enables fast experimentation on common datasets. It comes with a source code thats supports a large range of datasets and architectures, and a set of recipes to reproduce some important papers. Building blocks are thought and designed to be seamlessly plugged together. Filterbanks, encoders, maskers, decoders and losses are all common building blocks that can be combined in a...
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  • 4
    xTuring

    xTuring

    Easily build, customize and control your own LLMs

    xTuring is an open-source AI personalization software. xTuring makes it easy to build and control LLMs by providing a simple interface to personalize LLMs to your own data and application. xTuring provides fast, efficient and simple fine-tuning of LLMs, such as LLaMA, GPT-J, Galactica, and more. By providing an easy-to-use interface for fine-tuning LLMs to your own data and application, xTuring makes it simple to build, customize and control LLMs. The entire process can be done inside your...
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  • Propel Software: Product Value Management Platform for Manufacturers Icon
    Propel Software: Product Value Management Platform for Manufacturers

    For modern product companies that need to connect product and commercial teams successfully

    Propel is a cloud-native Product Value Management platform that unifies PLM, QMS, and PIM in one connected system, giving manufacturers complete visibility and control across the entire product lifecycle. It provides a single source of truth for all product data, streamlines change management, strengthens quality and compliance processes, and accelerates time-to-market by eliminating the silos and manual steps that slow teams down.
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  • 5
    State of Open Source AI

    State of Open Source AI

    Clarity in the current fast-paced mess of Open Source innovation

    This repository is the source for a book (or large written work) titled “The State of Open Source AI”. The goal of the project is to bring clarity to the rapidly evolving open-source AI ecosystem by documenting trends, models, tools, standards, deployment practices, and challenges. It acts as both a snapshot and a guide: readers can see what’s “hot now” in open AI infrastructure, what open licensing or governance issues are emerging, how deployment options compare, and what gaps remain....
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  • 6
    QuantResearch

    QuantResearch

    Quantitative analysis, strategies and backtests

    ...Many notebooks demonstrate backtesting pipelines that allow users to evaluate trading strategies using historical market data. The project integrates machine learning methods with traditional quantitative finance models, illustrating how statistical techniques can be applied to asset management and trading.
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  • 7
    PyTorch Implementation of SDE Solvers

    PyTorch Implementation of SDE Solvers

    Differentiable SDE solvers with GPU support and efficient sensitivity

    This library provides stochastic differential equation (SDE) solvers with GPU support and efficient backpropagation. examples/demo.ipynb gives a short guide on how to solve SDEs, including subtle points such as fixing the randomness in the solver and the choice of noise types. examples/latent_sde.py learns a latent stochastic differential equation, as in Section 5 of [1]. The example fits an SDE to data, whilst regularizing it to be like an Ornstein-Uhlenbeck prior process. The model can be...
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  • 8
    YoloV3 Implemented in TensorFlow 2.0

    YoloV3 Implemented in TensorFlow 2.0

    YoloV3 Implemented in Tensorflow 2.0

    YoloV3 Implemented in TensorFlow 2.0 is built using TensorFlow 2.0. The project provides a modern deep learning implementation of the popular YOLOv3 algorithm, which is widely used for real-time object detection in images and video streams. YOLOv3 works by dividing an image into grid regions and predicting bounding boxes and class probabilities simultaneously, allowing objects to be detected quickly and efficiently. The repository includes training scripts, inference tools, and configuration...
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  • 9
    ChatFred

    ChatFred

    Alfred workflow using ChatGPT, DALL·E 2 and other models for chatting

    Alfred workflow using ChatGPT, DALL·E 2 and other models for chatting, image generation and more. Access ChatGPT, DALL·E 2, and other OpenAI models. Language models often give wrong information. Verify answers if they are important. Talk with ChatGPT via the cf keyword. Answers will show as Large Type. Alternatively, use the Universal Action, Fallback Search, or Hotkey. To generate text with InstructGPT models and see results in-line, use the cft keyword. ⤓ Install on the Alfred Gallery or...
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  • Quality and compliance software for growing life science companies Icon
    Quality and compliance software for growing life science companies

    Unite quality management, product lifecycle, and compliance intelligence to stay continuously audit-ready and accelerate market entry

    Automate gap analysis across FDA, ISO 13485, MDR, and 28+ regulatory standards. Cross-map evidence once, reuse across submissions. Get real-time risk alerts and board-ready dashboards, so you can expand into new markets with confidence
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  • 10
    funNLP

    funNLP

    Resources, corpora, and tools for Chinese natural language processing

    ...Its value lies in providing not just tools but also curated, domain-specific data, which can be hard to find elsewhere.
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  • 11
    AnyTrading

    AnyTrading

    The most simple, flexible, and comprehensive OpenAI Gym trading

    gym-anytrading is an OpenAI Gym-compatible environment designed for developing and testing reinforcement learning algorithms on trading strategies. It simulates trading environments for financial markets, including stocks and forex.
    Downloads: 4 This Week
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  • 12
    Lightning-Hydra-Template

    Lightning-Hydra-Template

    PyTorch Lightning + Hydra. A very user-friendly template

    Convenient all-in-one technology stack for deep learning prototyping - allows you to rapidly iterate over new models, datasets and tasks on different hardware accelerators like CPUs, multi-GPUs or TPUs. A collection of best practices for efficient workflow and reproducibility. Thoroughly commented - you can use this repo as a reference and educational resource. Not fitted for data engineering - the template configuration setup is not designed for building data processing pipelines that...
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  • 13
    Detic

    Detic

    Code release for "Detecting Twenty-thousand Classes

    Detic (“Detecting Twenty-thousand Classes using Image-level Supervision”) is a large-vocabulary object detector that scales beyond fully annotated datasets by leveraging image-level labels. It decouples localization from classification, training a strong box localizer on standard detection data while learning classifiers from weak supervision and large image-tag corpora. A shared region proposal backbone feeds a flexible classification head that can expand to tens of thousands of categories...
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  • 14
    find-similar

    find-similar

    User-friendly library to find similar objects

    The mission of the FindSimilar project is to provide a powerful and versatile open source library that empowers developers to efficiently find similar objects and perform comparisons across a variety of data types. Whether dealing with texts, images, audio, or more, our project aims to simplify the process of identifying similarities and enhancing decision-making. https://github.com/findsimilar/find-similar - GitHub repo http://demo.findsimilar.org/ - Demo project and...
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  • 15
    LangChain Apps on Production with Jina

    LangChain Apps on Production with Jina

    Langchain Apps on Production with Jina & FastAPI

    Jina is an open-source framework for building scalable multi-modal AI apps on Production. LangChain is another open-source framework for building applications powered by LLMs. long-chain-serve helps you deploy your LangChain apps on Jina AI Cloud in a matter of seconds. You can benefit from the scalability and serverless architecture of the cloud without sacrificing the ease and convenience of local development. And if you prefer, you can also deploy your LangChain apps on your own...
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  • 16
    Consistency Models

    Consistency Models

    Official repo for consistency models

    consistency_models is the repository for Consistency Models, a new family of generative models introduced by OpenAI that aim to generate high-quality samples by mapping noise directly into data — circumventing the need for lengthy diffusion chains. It builds on and extends diffusion model frameworks (e.g. based on the guided-diffusion codebase), adding techniques like consistency distillation and consistency training to enable fast, often one-step, sample generation. The repo is implemented...
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  • 17
    PromethAI

    PromethAI

    Open-source framework that gives you AI Agents

    PromethAI-Backend is a backend framework for AI-driven automation and knowledge extraction. It is designed to integrate with large language models (LLMs) to provide AI-enhanced workflows, including content generation, summarization, and data analysis.
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  • 18
    MetaTransformer

    MetaTransformer

    Meta-Transformer for Unified Multimodal Learning

    We're thrilled to present OneLLM, an ensembling Meta-Transformer framework with Multimodal Large Language Models, which performs multimodal joint training, supports more modalities including fMRI, Depth, and Normal Maps, and demonstrates very impressive performances on 25 benchmarks.
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  • 19
    ThoughtSource

    ThoughtSource

    A central, open resource for data and tools

    ThoughtSource is a central, open resource and community centered on data and tools for chain-of-thought reasoning in large language models (Wei 2022). Our long-term goal is to enable trustworthy and robust reasoning in advanced AI systems for driving scientific research and medical practice.
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  • 20
    macara

    macara

    A converter for seamless transformation of files, data, and media ...

    This application consolidates various scripts, including an AI feature (rembg), into a singular platform. The design of this software is evolutionary, allowing for the seamless integration of additional scripts, menus, or windows as needed. Serving as a versatile tool, it facilitates efficient file management, especially when handling a substantial volume of images, whether sorting by name or other attributes. These scripts are crafted to complement generative art AI technologies like Dall-e...
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  • 21
    Chinese-LLaMA-Alpaca-2 v2.0

    Chinese-LLaMA-Alpaca-2 v2.0

    Chinese LLaMA & Alpaca large language model + local CPU/GPU training

    This project has open-sourced the Chinese LLaMA model and the Alpaca large model with instruction fine-tuning to further promote the open research of large models in the Chinese NLP community. Based on the original LLaMA , these models expand the Chinese vocabulary and use Chinese data for secondary pre-training, which further improves the basic semantic understanding of Chinese. At the same time, the Chinese Alpaca model further uses Chinese instruction data for fine-tuning, which...
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  • 22
    AI Explainability 360

    AI Explainability 360

    Interpretability and explainability of data and machine learning model

    The AI Explainability 360 toolkit is an open-source library that supports the interpretability and explainability of datasets and machine learning models. The AI Explainability 360 Python package includes a comprehensive set of algorithms that cover different dimensions of explanations along with proxy explainability metrics. The AI Explainability 360 interactive experience provides a gentle introduction to the concepts and capabilities by walking through an example use case for different consumer personas. The tutorials and example notebooks offer a deeper, data scientist-oriented introduction. ...
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  • 23
    Lightning Flash

    Lightning Flash

    Flash enables you to easily configure and run complex AI recipes

    Your PyTorch AI Factory, Flash enables you to easily configure and run complex AI recipes for over 15 tasks across 7 data domains. In a nutshell, Flash is the production-grade research framework you always dreamed of but didn't have time to build. All data loading in Flash is performed via a from_* classmethod on a DataModule. Which DataModule to use and which from_* methods are available depends on the task you want to perform. For example, for image segmentation where your data is stored...
    Downloads: 2 This Week
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  • 24
    CausalNex

    CausalNex

    A Python library that helps data scientists to infer causation

    CausalNex is a Python library that uses Bayesian Networks to combine machine learning and domain expertise for causal reasoning. You can use CausalNex to uncover structural relationships in your data, learn complex distributions, and observe the effect of potential interventions.
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  • 25
    hloc

    hloc

    Visual localization made easy with hloc

    This is hloc, a modular toolbox for state-of-the-art 6-DoF visual localization. It implements Hierarchical Localization, leveraging image retrieval and feature matching, and is fast, accurate, and scalable. This codebase won the indoor/outdoor localization challenges at CVPR 2020 and ECCV 2020, in combination with SuperGlue, our graph neural network for feature matching. We provide step-by-step guides to localize with Aachen, InLoc, and to generate reference poses for your own data using...
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