Showing 1214 open source projects for "python data analysis"

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  • 1
    DOLMA

    DOLMA

    Data and tools for generating and inspecting OLMo pre-training data

    DOLMA (Data Optimization and Learning for Model Alignment) is a framework designed to manage large-scale datasets for training and fine-tuning language models efficiently.
    Downloads: 4 This Week
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  • 2
    A.I.G

    A.I.G

    Full-stack AI Red Teaming platform

    AI-Infra-Guard is a powerful open-source security platform from Tencent’s Zhuque Lab designed to assess the safety and resilience of AI infrastructures, codebases, and components through automated scanning and evaluation tools. It brings together AI infrastructure vulnerability scanning, MCP server risk analysis, and jailbreak evaluation into a unified workflow so that enterprises and individuals can identify critical security issues without relying on external services. Users can deploy it...
    Downloads: 5 This Week
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  • 3
    ClearML

    ClearML

    Streamline your ML workflow

    ClearML is an open source platform that automates and simplifies developing and managing machine learning solutions for thousands of data science teams all over the world. It is designed as an end-to-end MLOps suite allowing you to focus on developing your ML code & automation, while ClearML ensures your work is reproducible and scalable. The ClearML Python Package for integrating ClearML into your existing scripts by adding just two lines of code, and optionally extending your experiments and other workflows with ClearML powerful and versatile set of classes and methods. ...
    Downloads: 2 This Week
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  • 4
    YData Synthetic

    YData Synthetic

    Synthetic data generators for tabular and time-series data

    ...It consists a set of different GANs architectures developed using Tensorflow 2.0. Several example Jupyter Notebooks and Python scripts are included, to show how to use the different architectures. YData synthetic has now a UI interface to guide you through the steps and inputs to generate structure tabular data. The streamlit app is available form v1.0.0 onwards.
    Downloads: 0 This Week
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  • 5
    DeiT (Data-efficient Image Transformers)
    DeiT (Data-efficient Image Transformers) shows that Vision Transformers can be trained competitively on ImageNet-1k without external data by using strong training recipes and knowledge distillation. Its key idea is a specialized distillation strategy—including a learnable “distillation token”—that lets a transformer learn effectively from a CNN or transformer teacher on modest-scale datasets. The project provides compact ViT variants (Tiny/Small/Base) that achieve excellent...
    Downloads: 0 This Week
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  • 6
    GraphRAG

    GraphRAG

    A modular graph-based Retrieval-Augmented Generation (RAG) system

    The GraphRAG project is a data pipeline and transformation suite that is designed to extract meaningful, structured data from unstructured text using the power of LLMs.
    Downloads: 4 This Week
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  • 7
    PrivateGPT

    PrivateGPT

    Interact with your documents using the power of GPT

    PrivateGPT is a production-ready, privacy-first AI system that allows querying of uploaded documents using LLMs, operating completely offline in your own environment. It provides contextual generative AI capabilities without sending data externally. Now maintained under Zylon.ai with enterprise deployment options (air gapped, cloud, or on-prem).
    Downloads: 16 This Week
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  • 8
    PySINDy

    PySINDy

    A package for the sparse identification of nonlinear dynamical systems

    PySINDy is a Python library that implements the Sparse Identification of Nonlinear Dynamics (SINDy) method for discovering mathematical models of dynamical systems from data. The framework focuses on identifying governing equations that describe the behavior of complex physical systems by selecting sparse combinations of candidate functions. Instead of fitting a purely predictive machine learning model, PySINDy attempts to recover interpretable differential equations that explain how a system evolves over time. ...
    Downloads: 2 This Week
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  • 9
    SDGym

    SDGym

    Benchmarking synthetic data generation methods

    The Synthetic Data Gym (SDGym) is a benchmarking framework for modeling and generating synthetic data. Measure performance and memory usage across different synthetic data modeling techniques – classical statistics, deep learning and more! The SDGym library integrates with the Synthetic Data Vault ecosystem. You can use any of its synthesizers, datasets or metrics for benchmarking. You also customize the process to include your own work. Select any of the publicly available datasets from the...
    Downloads: 4 This Week
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  • 10
    OpenPlanter

    OpenPlanter

    Language-model investigation agent with a terminal UI

    OpenPlanter is an open-source Python project focused on building an intelligent automated planting or gardening system powered by software control and data processing. The repository is designed to help developers and hobbyists create programmable plant management workflows that can monitor, schedule, and optimize growing conditions. It emphasizes automation and extensibility, allowing integration with sensors, environmental data, and control logic for smart cultivation setups. ...
    Downloads: 1 This Week
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  • 11
    Vanna 2.0

    Vanna 2.0

    Chat with your SQL database

    ...Vanna can be integrated into many environments, including notebooks, web applications, messaging platforms, and data dashboards, making it flexible for analytics and data exploration workflows. The system streams query results, visualizations, and summaries directly to user interfaces, allowing non-technical users to interact with complex data systems through conversational queries. It also includes enterprise-grade features such as user-aware security, permission enforcement, and query auditing for production deployments.
    Downloads: 4 This Week
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  • 12
    Ragas

    Ragas

    Supercharge Your LLM Application Evaluations

    Objective metrics, intelligent test generation, and data-driven insights for LLM apps. Ragas is your ultimate toolkit for evaluating and optimizing Large Language Model (LLM) applications. Say goodbye to time-consuming, subjective assessments and hello to data-driven, efficient evaluation workflows. Don't have a test dataset ready? We also do production-aligned test set generation.
    Downloads: 5 This Week
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  • 13
    nesa

    nesa

    Run AI models end-to-end encrypted

    nesa is an open-source initiative focused on building decentralized AI infrastructure that enables secure, verifiable, and privacy-preserving machine learning and inference across distributed environments. The project aims to address key challenges in modern AI systems, such as data privacy, trust, and centralization, by leveraging cryptographic techniques and decentralized architectures. NESA allows developers to run AI computations in a way that ensures data integrity and confidentiality,...
    Downloads: 3 This Week
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  • 14
    Local File Organizer

    Local File Organizer

    An AI-powered file management tool that ensures privacy

    ...Through AI-driven analysis, the software can detect themes, topics, and metadata in files, allowing it to organize information in ways that traditional rule-based file managers cannot achieve. The tool supports multiple sorting strategies that allow users to categorize files by content, date, or type depending on their workflow preferences.
    Downloads: 0 This Week
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  • 15
    LitterBox

    LitterBox

    A secure sandbox environment for malware developers and red teamers

    LitterBox is a controlled malware-analysis and payload-testing sandbox aimed at red teams who need to validate evasions and behaviors before deployment. It provides an isolated environment to exercise payloads against modern detection stacks, verify signatures and heuristics, and observe runtime characteristics without leaking binaries to third-party vendors. The README frames typical use cases: testing evasion, validating detections, analyzing behavior, and keeping sensitive tooling...
    Downloads: 1 This Week
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  • 16
    Binary Ninja MCP

    Binary Ninja MCP

    A Binary Ninja plugin, MCP server

    The Binary Ninja MCP is a plugin and bridge that integrates Binary Ninja with Large Language Model clients via the Model Context Protocol, enhancing reverse engineering workflows with AI assistance. ​
    Downloads: 6 This Week
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  • 17
    supervision

    supervision

    We write your reusable computer vision tools

    We write your reusable computer vision tools. Whether you need to load your dataset from your hard drive, draw detections on an image or video, or count how many detections are in a zone. You can count on us.
    Downloads: 4 This Week
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  • 18
    n8n

    n8n

    Free and source-available fair-code licensed workflow automation tool

    n8n is an extendable workflow automation tool. With a fair-code distribution model, n8n will always have visible source code, be available to self-host, and allow you to add your own custom functions, logic and apps. n8n's node-based approach makes it highly versatile, enabling you to connect anything to everything. n8n has 200+ different nodes to automate workflows.
    Downloads: 819 This Week
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  • 19
    PaperAI

    PaperAI

    Semantic search and workflows for medical/scientific papers

    PaperAI is an open-source framework for searching and analyzing scientific papers, particularly useful for researchers looking to extract insights from large-scale document collections.
    Downloads: 4 This Week
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  • 20
    Causal ML

    Causal ML

    Uplift modeling and causal inference with machine learning algorithms

    Causal ML is a Python package that provides a suite of uplift modeling and causal inference methods using machine learning algorithms based on recent research [1]. It provides a standard interface that allows users to estimate the Conditional Average Treatment Effect (CATE) or Individual Treatment Effect (ITE) from experimental or observational data.
    Downloads: 6 This Week
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  • 21
    Unstructured.IO

    Unstructured.IO

    Open source libraries and APIs to build custom preprocessing pipelines

    The unstructured library provides open-source components for ingesting and pre-processing images and text documents, such as PDFs, HTML, Word docs, and many more. The use cases of unstructured revolve around streamlining and optimizing the data processing workflow for LLMs. unstructured modular bricks and connectors form a cohesive system that simplifies data ingestion and pre-processing, making it adaptable to different platforms and is efficient in transforming unstructured data into...
    Downloads: 9 This Week
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  • 22
    MCP Atlassian

    MCP Atlassian

    MCP server that integrates Confluence and Jira

    The MCP Atlassian server integrates Atlassian products like Confluence and Jira with the Model Context Protocol. It supports both Cloud and Server/Data Center deployments, enabling AI models to interact with these platforms securely. ​
    Downloads: 7 This Week
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  • 23
    Physical Symbolic Optimization (Φ-SO)

    Physical Symbolic Optimization (Φ-SO)

    Physical Symbolic Optimization

    Physical Symbolic Optimization (Φ-SO) - A symbolic optimization package built for physics. Symbolic regression module uses deep reinforcement learning to infer analytical physical laws that fit data points, searching in the space of functional forms.
    Downloads: 0 This Week
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  • 24
    Toloka-Kit

    Toloka-Kit

    Toloka-Kit is a Python library for working with Toloka API

    ...Toloka entities are represented as Python classes. You can use them instead of accessing the API using JSON representations. There’s no need to validate JSON files and work with them directly. Support of both synchronous and asynchronous (via async/await) executions. Streaming support: build complex pipelines which send and receive data in real-time. For example, you can pass data between two related projects: one for data labeling, and another for its validation. ...
    Downloads: 0 This Week
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  • 25
    uqlm

    uqlm

    Uncertainty Quantification for Language Models, is a Python package

    UQLM is a Python library developed to detect hallucinations and quantify uncertainty in the outputs of large language models. The system implements a variety of uncertainty quantification techniques that assign confidence scores to model responses. These scores help developers determine how likely a generated answer is to contain errors or fabricated information.
    Downloads: 6 This Week
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