Search Results for "data driven"
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Showing 91 open source projects for "data driven"
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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Data-Juicer
Data processing for and with foundation models
Data-Juicer is an open-source data processing and augmentation framework designed to enhance the quality and diversity of datasets for machine learning tasks. It includes a modular pipeline for scalable data transformation. -
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Agentic Data Scientist
An end-to-end Data Scientist
Agentic Data Scientist is an experimental AI-driven research framework that orchestrates data science workflows through autonomous agents that can reason, plan, and execute complex analytics tasks. Unlike traditional scripted pipelines, this project lets AI agents break down high-level research goals into sub-tasks such as data acquisition, cleaning, modeling, evaluation, and reporting, with minimal human direction. -
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DeepBI
LLM based data scientist, AI native data application
DeepBI is an AI-native data analysis platform. DeepBI leverages the power of large language models to explore, query, visualize, and share data from any data source. Users can use DeepBI to gain data insight and make data-driven decisions. -
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MLE-bench
AI multi-agent framework for automating data-driven R&D workflows
RD-Agent is an open source AI framework designed to automate research and development workflows in data-driven domains. It uses large language models and multiple collaborating agents to simulate the typical cycle of research, experimentation, and improvement that human data scientists follow. It separates the process into two core phases: a research stage that proposes hypotheses and ideas, and a development stage that implements and evaluates them through code execution and experiments. ... -
Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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DATAGEN
AI-driven multi-agent research assistant automating hypothesis
DATAGEN is an AI-driven multi-agent research and data analysis platform designed to automate complex analytical workflows. The system coordinates multiple specialized AI agents that collaborate to perform tasks such as hypothesis generation, data collection, analysis, visualization, and report creation. Instead of requiring users to manually orchestrate each stage of a research process, the platform allows these agents to coordinate automatically and handle the workflow end-to-end. ... -
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AgentForge
Extensible AGI Framework
AgentForge is a framework for creating and deploying AI agents that can perform autonomous decision-making and task execution. It enables developers to define agent behaviors, train models, and integrate AI-powered automation into various applications. -
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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. -
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Solace Agent Mesh
An event-driven framework designed to build multi-agent AI systems
Solace Agent Mesh is an event-driven framework designed to build, orchestrate, and scale multi-agent AI systems where specialized agents collaborate to solve complex tasks across distributed environments. It addresses one of the main challenges in modern AI systems, which is connecting isolated agents, data sources, and enterprise systems into a cohesive and interoperable ecosystem. -
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Clay Foundation Model
The Clay Foundation Model - An open source AI model and interface
The Clay Foundation Model is an open-source AI model and interface designed to provide comprehensive data and insights about Earth. It aims to serve as a foundational tool for environmental monitoring, research, and decision-making by integrating various data sources and offering an accessible platform for analysis. -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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Agently 4
Build GenAI application quick and easy
...It is licensed under Apache-2.0, allowing commercial use and modification. Because it's built in Python, it integrates easily with existing data pipelines, databases, and agent architectures. -
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Logfire MCP
The Logfire MCP Server is here
The Logfire MCP Server is a Model Context Protocol server that allows AI applications to access OpenTelemetry traces and metrics sent to Logfire. It enables retrieval and analysis of telemetry data, enhancing debugging and observability workflows. -
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NVIDIA PhysicsNeMo
Open-source deep-learning framework for building and training
...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 pipelines for models that combine data-driven learning with physics-based constraints. It is built on top of the PyTorch ecosystem and integrates with GPU-accelerated computing environments to handle computationally demanding simulations and datasets. The framework supports a wide range of scientific applications, including computational fluid dynamics, climate modeling, weather prediction, and engineering simulations. -
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DeerFlow
Deep Research framework, combining language models with tools
DeerFlow is an open-source, community-driven “deep research” framework / multi-agent orchestration platform developed by ByteDance. It aims to combine the reasoning power of large language models (LLMs) with automated tool-use — such as web search, web crawling, Python execution, and data processing — to enable complex, end-to-end research workflows. Instead of a monolithic AI assistant, DeerFlow defines multiple specialized agents (e.g. -
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Browser Use
Make websites accessible for AI agents
...Its cloud offering includes advanced capabilities like stealth browsing, CAPTCHA solving, and proxy rotation for reliable automation. Overall, Browser Use transforms web interaction into an intelligent, programmable workflow driven by AI agents. -
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FL4Health
Library to facilitate federated learning research
FL4Health is a Vector Institute toolkit for building modular, clinically-focused FL pipelines. Tailored for healthcare, it supports privacy-preserving FL, heterogeneous data settings, integrated reporting, and clear API design. -
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Vibe-Trading
Vibe-Trading: Your Personal Trading Agent
...Overall, it delivers an end-to-end AI-driven trading environment for both research and execution. -
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Open Gauss
Project-scoped Lean workflow orchestrator from Math, Inc.
Open Gauss is an enterprise-grade open-source relational database management system designed to handle large-scale data processing with high performance, reliability, and security. It is based on the PostgreSQL ecosystem but significantly extends its capabilities through architectural optimizations, AI-driven features, and enterprise-level enhancements. The database organizes data using the relational model, storing structured information in tables composed of rows and columns while supporting standard SQL for querying and management. ... -
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NVIDIA Earth2Studio
Open-source deep-learning framework
NVIDIA Earth2Studio is an open-source Python package and framework designed to accelerate the development and deployment of AI-driven weather and climate science workflows. It provides a unified API that lets researchers, data scientists, and engineers build complex forecasting and analysis pipelines by combining modular prognostic and diagnostic AI models with a diverse range of real-world data sources such as global forecast systems, reanalysis datasets, and satellite feeds. ... -
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CS-Ebook
Curated list of classic, high-quality computer science books
CS-Ebook is a curated repository that compiles high-quality and classic computer science books across a wide range of software-related fields. It focuses on depth over volume, selecting only well-regarded titles that support structured learning and long-term skill development. It spans core areas such as computer fundamentals, programming languages, software engineering, mathematics, data science, and artificial intelligence, making it suitable for learners at different stages. Rather than... -
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OpenChronicle
Open-source, local-first memory for any tool-capable LLM agent
...The system emphasizes visualization and organization of complex information over time. It can be used for research, writing, or personal knowledge tracking. OpenChronicle supports extensibility, enabling customization of how data is structured and displayed. It encourages users to build rich, interconnected knowledge systems. Overall, it transforms static notes into dynamic, timeline-driven narratives. -
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Vanna
Chat with your SQL database
Vanna.AI is an AI-powered tool for natural language database querying, enabling users to interact with databases using simple English queries. It converts natural language questions into SQL queries, making data access more intuitive for non-technical users. -
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Thoth
Thoth - Personal AI Sovereignty. A local-first AI assistant
Thoth is an AI-driven system designed to support advanced reasoning, knowledge processing, or agentic workflows, likely inspired by the concept of structured intelligence and decision-making. It focuses on organizing and synthesizing information in a way that enables deeper insights and more autonomous behavior. The project may incorporate LLMs, data pipelines, and modular components to handle complex tasks such as reasoning, planning, or knowledge retrieval. -
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Quantitative Trading System
A comprehensive quantitative trading system with AI-powered analysis
Quantitative Trading System is a comprehensive quantitative trading platform that integrates artificial intelligence, financial data analysis, and automated strategy execution within a unified software system. The project is designed to provide an end-to-end infrastructure for building and operating algorithmic trading strategies in financial markets. It includes tools for collecting and processing market data from multiple sources, performing statistical and machine learning analysis, and... -
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OpenPlanter
Language-model investigation agent with a terminal UI
...With its modular Python codebase, users can adapt the platform for different plant types, hardware setups, or automation strategies. Overall, OpenPlanter aims to simplify the creation of programmable, data-driven plant care systems. -
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txtai
Build AI-powered semantic search applications
...Machine-learning pipelines to run extractive question-answering, zero-shot labeling, transcription, translation, summarization and text extraction. Cloud-native architecture that scales out with container orchestration systems (e.g. Kubernetes). Applications range from similarity search to complex NLP-driven data extractions to generate structured databases. The following applications are powered by txtai.