Search Results for "data driven"
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Showing 856 open source projects for "data driven"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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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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Spring Data REST
Simplifies building hypermedia-driven REST web services
Spring Data REST is part of the umbrella Spring Data project and makes it easy to build hypermedia-driven REST web services on top of Spring Data repositories. Spring Data REST builds on top of Spring Data repositories, analyzes your application’s domain model and exposes hypermedia-driven HTTP resources for aggregates contained in the model. -
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a-stock-data
Full-stack China A-Share data toolkit for AI coding assistants
...It is designed to work with tools such as Claude Code, Codex, and OpenClaw through context-injected Markdown and embedded Python. The repository emphasizes tested endpoints and practical usability for agent-driven financial analysis workflows. Its main value is turning fragmented A-share data sources into a unified toolset for AI-assisted research and coding. -
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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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Spring Data Redis
Provides support to increase developer productivity in Java
Provides support to increase developer productivity in Java when using Redis, a key-value store. Uses familiar Spring concepts such as a template class for core API usage and lightweight repository-style data access. The primary goal of the Spring Data project is to make it easier to build Spring-powered applications that use new data access technologies such as non-relational databases, map-reduce frameworks, and cloud-based data services. Connection package as low-level abstraction across multiple Redis drivers (Lettuce and Jedis). Exception translation to Spring’s portable Data Access exception hierarchy for Redis driver exceptions. ... -
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data-table-filters
Faceted filters, sorting & infinite scroll for React data tables
...The tool also supports customization, allowing developers to tailor filtering logic and UI behavior to their specific needs. Its modular design makes it easy to integrate into existing projects without major refactoring. Overall, Data Table Filters enhances data-driven applications by providing flexible and scalable filtering solutions. -
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Malli
High-performance data-driven data specification library
Malli is a powerful, data-driven schema library for Clojure and ClojureScript, offering rich support for specification, validation, parsing, error reporting, and generative testing. Designed for performance, Malli leverages efficient runtime representations and code generation, seamlessly integrating with Clojure’s data-oriented architecture. It supports function schemas, JSON transformation, and OpenAPI generation for strong API contracts. -
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AI Data Science Team
An AI-powered data science team of agents
AI Data Science Team is a Python library and agent ecosystem designed to accelerate and automate common data science workflows by modeling them as specialized AI “agents” that can be orchestrated to perform tasks like data cleaning, transformation, analysis, visualization, and machine learning. It provides a modular agent framework where each agent focuses on a step in the typical data science pipeline — for example, loading data from CSV/Excel files, cleaning and wrangling messy datasets, engineering predictive features, building models with AutoML, connecting to SQL databases, and producing visual outputs — all driven by natural language or programmatic instructions. ... -
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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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Apollo Client
Use GraphQL to build client applications
GraphQL client that will allow you to easily use data from GraphQL with any JavaScript frontend. -
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Orx: Data-Driven Game Engine
Orx: Data-Driven Game Engine
Orx is a portable, lightweight, plugin-based, data-driven and extremely easy to use 2D-oriented game engine. As orx is data driven, it allows users to create games with a small number of lines of code and reduces drastically the development time. -
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ValueCell
Community-driven, multi-agent platform for financial applications
ValueCell is a community-driven multi-agent AI platform focused on financial research, analysis, and decision-making that lets users leverage multiple specialized AI agents for tasks like data retrieval, investment research, strategy execution, and market tracking. The system brings together a suite of collaborative agents—such as research agents that gather and interpret fundamentals, strategy agents that implement trading logic, and news agents that deliver personalized updates—to help users make more informed financial decisions across stocks, crypto, and other markets. ... -
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Watermill
Building event-driven applications the easy way in Go
Go library for building event-driven applications. Our goal was to create a tool that is easy to understand, even by junior developers. It doesn't matter if you want to do Event-driven architecture, CQRS, Event Sourcing or just stream MySQL Binlog to Kafka. Watermill was designed to process hundreds of thousands of messages per second. Every component is built in a way that allows you to configure it for your needs. You can also implement your own middleware for the router. Watermill is... -
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Machine Learning and Data Science Apps
A curated list of applied machine learning and data science notebooks
This repository is a large curated collection of machine learning and data science resources focused on real-world industry applications. Instead of being a single software framework, it acts as a knowledge base containing links to practical projects, notebooks, datasets, and libraries that demonstrate how machine learning can be applied across different sectors. The repository organizes resources by industry categories such as finance, healthcare, agriculture, manufacturing, government, and... -
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Reitit
A fast data-driven routing library for Clojure/Script
Reitit is a fast, data-driven routing library for Clojure and ClojureScript, designed for seamless integration with Ring and other ecosystems. It offers declarative route definition, efficient path resolution, and flexible route metadata, enabling both server-side and client-side routing with high performance and extensibility. A Ring routing app with input & output coercion using data-specs. -
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BTC Trading Since 2020
Public BTC trading context since 2020
...The project emphasizes data-driven decision-making, providing tools and scripts to analyze trends, generate signals, and evaluate performance metrics. It is structured in a way that allows users to modify or extend strategies, making it suitable for both learning and experimentation. The system is particularly useful for individuals interested in quantitative trading and algorithmic finance. -
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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. ... -
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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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QFramework
Unity3D System Design Architecture
QFramework is to provide a set of simple, powerful, easy-to-use, SOLID principles, support domain-driven design (DDD), event-driven, data-driven, layered, MVC, CQRS, modular, easy-to-extend architecture, her source code is only Up to line 800, you can completely save it in your notes app. Presentation layer: ViewController layer. The IController interface is responsible for the performance when receiving input and state changes. In general, MonoBehaviour is the presentation layer. ... -
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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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Apollo Client
A fully-featured, production ready caching GraphQL client
Apollo Client is a comprehensive state management library for JavaScript that enables you to manage both local and remote data with GraphQL. Use it to fetch, cache, and modify application data, all while automatically updating your UI. Apollo Client helps you structure code in an economical, predictable, and declarative way that's consistent with modern development practices. The core Apollo Client library provides built-in integration with React, and the larger Apollo community maintains... -
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EpicReact.Dev
Build a ReactJS App workshop
...A guided workflow, driven by a node go script and INSTRUCTIONS.md, lets learners move between exercises and extra credit steps while the repository updates the working files for each stage. Extensive tests, using Jest in watch mode, help students verify their solutions and learn how to work with test-driven feedback. -
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Axon Framework
Framework for Evolutionary Message-Driven Microservices on the JVM
Axon provides a unified, productive way of developing Java applications that can evolve without significant refactoring from a monolith to Event-Driven microservices. Axon includes both a programming model as well as specialized infrastructure to provide enterprise-ready operational support for the programming model - especially for scaling and distributing mission-critical business applications. Axon is composed of the following concepts and products. Domain-Driven Design (DDD) defines many concepts and patterns that help design software effectively, in line with the business requirements. ... -
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GenStage
Producer and consumer actors with back-pressure for Elixir
GenStage is a specification and set of behaviours for building demand-driven data pipelines on the BEAM. It formalizes the roles of producers, consumers, and producer-consumers, using back-pressure so that fast producers don’t overwhelm downstream stages. Developers implement callbacks like handle_demand and handle_events to control how items are emitted, transformed, and consumed across asynchronous boundaries. -
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GridDB
GridDB is a next-generation open source database
...Multi-model architecture capable of supporting various data stores with time-series data-oriented and pluggable data stores for efficient real-time processing and management of huge amounts of time-series data at high frequency. Various architectural innovations, such as in-memory orientation with "memory as the main unit and disk as the secondary unit" and event-driven design with minimal overhead, have been incorporated to achieve processing capabilities that can handle petabyte-scale applications.
