Search Results for "ai data analyst" - Page 12

Showing 464 open source projects for "ai data analyst"

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  • 1
    Enferno

    Enferno

    Modern Flask framework optimized for AI-assisted development

    Enferno is a framework for building developer-first cloud backends using PostgreSQL and TypeScript. It offers primitives for defining data models, APIs, and access rules directly in code, enabling quick iteration and deployment. Enferno is designed to accelerate SaaS and internal tool development by combining the benefits of traditional backends with developer ergonomics.
    Downloads: 2 This Week
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  • 2
    AstronRPA

    AstronRPA

    Agent-ready RPA suite with visual workflow automation tools engine

    ...It enables automation of common desktop software and browser-based tasks, making it suitable for repetitive business operations and system integrations. Astron RPA includes a large library of reusable components that handle tasks such as user interface operations, data processing, and system interactions, allowing workflows to be assembled from modular building blocks. Astron RPA also integrates with intelligent agent systems so that automated processes and AI-driven workflows can work together in broader automation scenarios.
    Downloads: 2 This Week
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  • 3
    NautilusTrader

    NautilusTrader

    A high-performance algorithmic trading platform

    NautilusTrader is an open-source, high-performance, production-grade algorithmic trading platform, provides quantitative traders with the ability to backtest portfolios of automated trading strategies on historical data with an event-driven engine, and also deploy those same strategies live, with no code changes. The platform is 'AI-first', designed to develop and deploy algorithmic trading strategies within a highly performant and robust Python native environment. This helps to address the parity challenge of keeping the Python research/backtest environment, consistent with the production live trading environment. ...
    Downloads: 31 This Week
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  • 4
    Pedalboard

    Pedalboard

    A Python library for audio

    ...It supports the most popular audio file formats and a number of common audio effects out of the box and also allows the use of VST3® and Audio Unit formats for loading third-party software instruments and effects. pedalboard was built by Spotify’s Audio Intelligence Lab to enable using studio-quality audio effects from within Python and TensorFlow. Internally at Spotify, pedalboard is used for data augmentation to improve machine learning models and to help power features like Spotify’s AI DJ and AI Voice Translation. pedalboard also helps in the process of content creation, making it possible to add effects to audio without using a Digital Audio Workstation.
    Downloads: 6 This Week
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  • 5
    MetaCLIP

    MetaCLIP

    ICLR2024 Spotlight: curation/training code, metadata, distribution

    MetaCLIP is a research codebase that extends the CLIP framework into a meta-learning / continual learning regime, aiming to adapt CLIP-style models to new tasks or domains efficiently. The goal is to preserve CLIP’s strong zero-shot transfer capability while enabling fast adaptation to domain shifts or novel class sets with minimal data and without catastrophic forgetting. The repository provides training logic, adaptation strategies (e.g. prompt tuning, adapter modules), and evaluation...
    Downloads: 0 This Week
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  • 6
    Mistral Finetune

    Mistral Finetune

    Memory-efficient and performant finetuning of Mistral's models

    mistral-finetune is an official lightweight codebase designed for memory-efficient and performant finetuning of Mistral’s open models (e.g. 7B, instruct variants). It builds on techniques like LoRA (Low-Rank Adaptation) to allow customizing models without full parameter updates, which reduces GPU memory footprint and training cost. The repo includes utilities for data preprocessing (e.g. reformat_data.py), validation scripts, and example YAML configs for training variants like 7B base or...
    Downloads: 0 This Week
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  • 7
    Map-Anything

    Map-Anything

    MapAnything: Universal Feed-Forward Metric 3D Reconstruction

    Map-Anything is a universal, feed-forward transformer for metric 3D reconstruction that predicts a scene’s geometry and camera parameters directly from visual inputs. Instead of stitching together many task-specific models, it uses a single architecture that supports a wide range of 3D tasks—multi-image structure-from-motion, multi-view stereo, monocular metric depth, registration, depth completion, and more. The model flexibly accepts different input combinations (images, intrinsics, poses,...
    Downloads: 5 This Week
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  • 8
    Kor

    Kor

    LLM

    This is a half-baked prototype that “helps” you extract structured data from text using LLMs. Specify the schema of what should be extracted and provide some examples. Kor will generate a prompt, send it to the specified LLM and parse out the output. You might even get results back.
    Downloads: 0 This Week
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  • 9
    deepdoctection

    deepdoctection

    A Repo For Document AI

    DeepDoctection is a document AI framework that applies deep learning techniques to analyze and extract structured data from scanned documents, PDFs, and images. deepdoctection is a Python library that orchestrates document extraction and document layout analysis tasks using deep learning models. It does not implement models but enables you to build pipelines using highly acknowledged libraries for object detection, OCR and selected NLP tasks and provides an integrated frameworks for fine-tuning, evaluating and running models. ...
    Downloads: 0 This Week
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  • 10
    Albumentations

    Albumentations

    Fast image augmentation library and an easy-to-use wrapper

    Albumentations is a computer vision tool that boosts the performance of deep convolutional neural networks. Albumentations is a Python library for fast and flexible image augmentations. Albumentations efficiently implements a rich variety of image transform operations that are optimized for performance, and does so while providing a concise, yet powerful image augmentation interface for different computer vision tasks, including object classification, segmentation, and detection....
    Downloads: 1 This Week
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  • 11
    Chatterbox

    Chatterbox

    SoTA open-source TTS

    Chatterbox is Resemble AI's first production-grade open source TTS model. Licensed under MIT, Chatterbox has been benchmarked against leading closed-source systems like ElevenLabs and is consistently preferred in side-by-side evaluations. Whether you're working on memes, videos, games, or AI agents, Chatterbox brings your content to life. It's also the first open source TTS model to support emotion exaggeration control, a powerful feature that makes your voices stand out. Try it now on our...
    Downloads: 18 This Week
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  • 12
    Scrapling

    Scrapling

    An adaptive Web Scraping framework

    ...The framework includes advanced fetchers capable of bypassing anti-bot protections such as Cloudflare Turnstile using stealth and browser automation techniques. Its powerful spider system supports multi-session crawling, pause and resume functionality, and real-time streaming of scraped data. Scrapling combines high performance, memory efficiency, and extensive async support to deliver blazing-fast scraping workflows. With a developer-friendly API, CLI tools, MCP server integration for AI-assisted extraction, and Docker support, it offers a complete solution for modern web scrapers.
    Downloads: 4 This Week
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  • 13
    Transformer Debugger

    Transformer Debugger

    Tool for exploring and debugging transformer model behaviors

    Transformer Debugger (TDB) is a research tool developed by OpenAI’s Superalignment team to investigate and interpret the behaviors of small language models. It combines automated interpretability methods with sparse autoencoders, enabling researchers to analyze how specific neurons, attention heads, and latent features contribute to a model’s outputs. TDB allows users to intervene directly in the forward pass of a model and observe how such interventions change predictions, making it...
    Downloads: 1 This Week
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  • 14
    Materials Discovery: GNoME

    Materials Discovery: GNoME

    AI discovers 520000 stable inorganic crystal structures for research

    Materials Discovery (GNoME) is a large-scale research initiative by Google DeepMind focused on applying graph neural networks to accelerate the discovery of stable inorganic crystal materials. The project centers on Graph Networks for Materials Exploration (GNoME), a message-passing neural network architecture trained on density functional theory (DFT) data to predict material stability and energy formation. Using GNoME, DeepMind identified 381,000 new stable materials, later expanding the...
    Downloads: 5 This Week
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  • 15
    NVIDIA PhysicsNeMo

    NVIDIA PhysicsNeMo

    Open-source deep-learning framework for building and training

    NVIDIA PhysicsNeMo is an open-source deep learning framework designed for building artificial intelligence models that incorporate physical laws and scientific knowledge into machine learning workflows. The framework focuses on the emerging field of physics-informed machine learning, where neural networks are used alongside physical equations to model complex scientific systems. PhysicsNeMo provides modular Python components that allow developers to create scalable training and inference...
    Downloads: 5 This Week
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  • 16
    verl

    verl

    Volcano Engine Reinforcement Learning for LLMs

    VERL is a reinforcement-learning–oriented toolkit designed to train and align modern AI systems, from language models to decision-making agents. It brings together supervised fine-tuning, preference modeling, and online RL into one coherent training stack so teams can move from raw data to aligned policies with minimal glue code. The library focuses on scalability and efficiency, offering distributed training loops, mixed precision, and replay/buffering utilities that keep accelerators busy. ...
    Downloads: 4 This Week
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  • 17
    NeMo Retriever Library

    NeMo Retriever Library

    Document content and metadata extraction microservice

    NeMo Retriever Library is a scalable microservice framework designed for extracting, structuring, and enriching content from documents to support downstream generative AI applications. It processes various document types by splitting them into components such as text, tables, charts, and images, and then applies OCR and contextual analysis to convert them into structured data formats. The system is built on NVIDIA NIM microservices, enabling high-performance parallel processing and efficient handling of large datasets. ...
    Downloads: 2 This Week
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  • 18
    Qwen-2.5-VL

    Qwen-2.5-VL

    Qwen2.5-VL is the multimodal large language model series

    Qwen2.5 is a series of large language models developed by the Qwen team at Alibaba Cloud, designed to enhance natural language understanding and generation across multiple languages. The models are available in various sizes, including 0.5B, 1.5B, 3B, 7B, 14B, 32B, and 72B parameters, catering to diverse computational requirements. Trained on a comprehensive dataset of up to 18 trillion tokens, Qwen2.5 models exhibit significant improvements in instruction following, long-text generation...
    Downloads: 13 This Week
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  • 19
    Guardrails

    Guardrails

    Framework for validating and controlling LLM outputs in AI apps

    Guardrails is an open source Python framework designed to help developers build more reliable and controlled applications powered by large language models. It provides mechanisms for validating and constraining both the inputs sent to a model and the outputs generated by it, helping reduce risks such as harmful content, prompt injection, or inaccurate responses. Guardrails works by applying configurable guards that intercept and evaluate interactions with the model before results are...
    Downloads: 6 This Week
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  • 20
    Book5_Essentials-Probability-Statistics

    Book5_Essentials-Probability-Statistics

    The book 5 of statistics in simplicity

    ...Like the other books in the series, it blends mathematical explanation with Python-based experimentation. Overall, the project provides a practical statistical foundation for students advancing into AI and data science.
    Downloads: 0 This Week
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  • 21
    FlowLens MCP

    FlowLens MCP

    Open-source MCP server that gives your coding agent

    ...The MCP server then loads this captured “flow” and exposes it to the AI agent via the Model Context Protocol (MCP), letting the agent examine, search, filter, and reason about the session just as a human developer would, without needing the agent to re-run the flow or rely on minimal reproduction data (logs, screenshots).
    Downloads: 0 This Week
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  • 22
    MCP Neo4j

    MCP Neo4j

    Model Context Protocol with Neo4j

    An implementation of the Model Context Protocol with Neo4j, enabling natural language interactions with Neo4j databases and facilitating operations such as schema retrieval and Cypher query execution. ​
    Downloads: 0 This Week
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  • 23
    Awesome Free ChatGPT

    Awesome Free ChatGPT

    List of free ChatGPT mirror sites, continuously updated

    This is a curated directory of freely accessible ChatGPT-style services and mirror sites that offer AI chatbot interfaces without login or payment requirements. Resources often support multiple models like GPT-4, Claude, Gemini, and more. Data collected from multiple independent sites with descriptions and tags. Includes services with image upload and drawing capabilities. Aggregates free, no-login-required ChatGPT-like web services.
    Downloads: 1 This Week
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  • 24
    LLM Vision

    LLM Vision

    Visual intelligence for your home.

    LLM Vision is an open-source integration for Home Assistant that adds multimodal large language model capabilities to smart home environments. The project enables Home Assistant to analyze images, video files, and live camera feeds using vision-capable AI models. Instead of relying only on traditional object detection pipelines, it allows users to send prompts about visual content and receive contextual descriptions or answers about what is happening in camera footage. The system can process events from surveillance platforms such as Frigate and convert them into meaningful summaries, notifications, or structured data for automation workflows. ...
    Downloads: 0 This Week
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  • 25
    video2robot

    video2robot

    End-to-end pipeline converting generative videos

    video2robot is an end-to-end open-source pipeline that converts generative video or prompt-driven motion content into executable humanoid robot motion sequences, enabling researchers and developers to go from high-level action descriptions or videos to robot-ready motion data. The pipeline supports both prompt-to-video generation using models like Veo/Sora and video upload processing, followed by human pose extraction through a 3D pose model and retargeting of that motion to robot joints...
    Downloads: 0 This Week
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