Data-Centric-AI-Community/awesome-data-centric-ai
Open-Source Software, Tutorials, and Research on Data-Centric AI π€
β‘ Executive Summary & Quick Facts
Authoritative Sourceawesome-data-centric-ai is awesome-data-centric-ai is an open-source project written in Jupyter Notebook: Open-Source Software, Tutorials, and Research on Data-Centric AI π€..
| Repository | Data-Centric-AI-Community/awesome-data-centric-ai β |
|---|---|
| Primary Category | ai |
| Language & Stack | Jupyter Notebook |
| Software License | MIT |
| Community Traction | β 357 stars Β· β 51 forks Β· #10,707 globally |
| Maintenance | β Active (Last commit: Sep 29, 2026) Β· 0 open issues |
| Target Audience | Developers and engineering teams building with Jupyter Notebook, seeking reliable, tested, and actively maintained tooling for production workloads. |
Star History
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+10
STARS Β· LAST 30 DAYS
1
PER DAY
#13
MOST-STARRED Jupyter Notebook
| Window | 7 days | 30 days | 90 days |
|---|---|---|---|
| Stars gained | +0 | +10 | +90 |
| Per day | 1 | 1 | 1 |
| Forks gained | +0 | +3 | +10 |
awesome-data-centric-ai gained 10 stars in the last 30 days, about 1 a day, and now has 357. It is about 5 years old and has averaged roughly 71 stars a year. It ranks #13 among Jupyter Notebook repositories and #10,707 across all languages on GitHubRepo.
Trending Record
20
DAYS ON TRENDING
#4733
BEST RANK
Sep 29, 2026
FIRST APPEARANCE
Active
STATUS TODAY
awesome-data-centric-ai has maintained a continuous presence across global trending indexes, peaking at #4733. Below is the 30-day activity profile:
π‘ Overview
awesome-data-centric-ai is an open-source project written in Jupyter Notebook: Open-Source Software, Tutorials, and Research on Data-Centric AI π€.
Engineered for speed, consistency, and developer ease, it solves common hurdles in ai, artificial-intelligence, awesome. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.
β‘ Key Features
Optimized execution pipeline written in Jupyter Notebook for predictable speed.
Zero-friction configuration with comprehensive sensible defaults out of the box.
Cross-platform runtime support across Linux, macOS, and Windows environments.
Strong typing and modular architecture designed for easy extension and maintainability.
Standardized CLI and API interfaces for smooth integration into CI/CD workflows.
Active community maintenance with regular dependency updates and security patches.
π₯ Installation
$ git clone https://github.com/Data-Centric-AI-Community/awesome-data-centric-ai.git
cd awesome-data-centric-aiβ System Requirements
Platforms
- β’ macOS
- β’ Linux
- β’ Windows
Runtime & Dependencies
Jupyter Notebook environment and standard tooling
Architecture
x86_64, ARM64 (Apple Silicon & Graviton)
π§ How It Works
awesome-data-centric-ai coordinates its core functionality through a modular Jupyter Notebook pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.
π― Production Use Cases
Autonomous AI Agents
Orchestrate intelligent workflows and tool-calling routines with awesome-data-centric-ai.
Model Inference & Prompting
Integrate fast, local or cloud-hosted generative AI models directly into production code.
Context Memory & RAG
Augment language models with dynamic vector retrieval and structured project memory.
Developer Productivity
Automate repetitive engineering tasks, code generation, and test creation using AI agents.
π Getting Started
Install awesome-data-centric-ai using your package manager: `git clone https://github.com/Data-Centric-AI-Community/awesome-data-centric-ai.git`
Initialize your project workspace or configuration file for awesome-data-centric-ai.
Import awesome-data-centric-ai into your codebase or invoke it directly from your terminal.
Execute your test suite or run `awesome-data-centric-ai --help` to verify successful setup.
π Strengths
β οΈ Considerations
β Alternatives & Direct Competitors
π₯ Who Should Use This
Developers and engineering teams building with Jupyter Notebook, seeking reliable, tested, and actively maintained tooling for production workloads.
π Nearby in the Rankings
Data-Centric-AI-Community/awesome-data-centric-ai is currently ranked #10,707 by stars across every repository tracked on GitHubRepo. These are adjacent projects:
| Rank | Repository | Language | Stars | Action |
|---|---|---|---|---|
| #10,694 | GenieFramework/Stipple.jl | JavaScript | β 358 | Compare β |
| #10,694 | meilisearch/meilisearch-rails | Ruby | β 358 | Compare β |
| #10,694 | MobiFlight/MobiFlight-Connector | C# | β 358 | Compare β |
| #10,694 | 7c/fakefilter | TypeScript | β 358 | Compare β |
| #10,694 | surrealdb/surrealdb.js | TypeScript | β 358 | Compare β |
| #10,707 | Data-Centric-AI-Community/awesome-data-centric-ai This Project | Jupyter Notebook | β 357 | |
| #10,707 | robertrouse/theographic-bible-metadata | JavaScript | β 357 | Compare β |
| #10,707 | magento/inventory | PHP | β 357 | Compare β |
| #10,707 | modernuo/ModernUO | C# | β 357 | Compare β |
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Frequently Asked Questions
What does awesome-data-centric-ai do? +
Open-Source Software, Tutorials, and Research on Data-Centric AI π€
What language is awesome-data-centric-ai written in? +
The primary language is Jupyter Notebook. Topics include: ai, artificial-intelligence, awesome, awesome-list, data.
Is awesome-data-centric-ai actively maintained? +
Yes, the last recorded push was on Sep 29, 2026 with 0 open issues being tracked.
How many stars does awesome-data-centric-ai have? +
awesome-data-centric-ai has 357 stars and 51 forks on GitHub.
How does awesome-data-centric-ai rank among GitHub repositories? +
With 357 stars, Data-Centric-AI-Community/awesome-data-centric-ai is ranked #10,707 globally across all repositories tracked on GitHubRepo and #13 among Jupyter Notebook projects.
What license is awesome-data-centric-ai distributed under? +
The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.
