Learn more about Data-Centric AI

Data-Centric AI is the systematic engineering of better data (via AI and automation). Learn about key concepts, useful tricks, and helpful tools.

How to run Large Language Models on Your Laptop?

Ollama is an open-source project that enables running various LLMs locally. It provides greater control over data privacy and security, is more cost-effective, and allows for experimentation. Ollama is available on macOS, Linux, and as a Docker container.

Navigating the Synthetic Data Landscape: How to Enhance Model Training and Data Quality

Learn about the uses and limitations of synthetic data in training machine learning models. This article covers how synthetic data can help with privacy and cost concerns, and offers practical tips for maintaining data quality.

The Critical Role of Data Curation in AI and Analytics

How are leading organizations like OpenAI, Google, Tesla are able to produce amazing models? By ensuring super high-quality data via extensive curation efforts. Here's how such efforts can now be automated via software.

The Benefits of No Code Development Solutions for Data Correction

Cleanlab Studio offers a no-code development solution to power data correction. Why did we choose this direction?

How to Improve Data Quality Through Data Correction: A Primer

Explore the process and benefits of thorough data correction and discover our comprehensive solutions to gain better control over your data.

Elevating Data Quality: The Crucial Role of Proper Data Annotation

Mislabeled data can lead to a slew of costly issues. Learn about the potential problems along with data annotation best practices here.

The 8 Most Common Data Quality Issues

Learn about common issues that plague datasets and how they cost companies millions of dollars.

Machine Learning Deployment: How to Find Reliable Data

Uncover how to refine and capitalize on even the most complex datasets to empower your ML deployment with actionable insights.

A Guide to Data-Centric AI

Learn about the concepts, use cases, and future of data-centric AI.

Establishing Robust Data and AI Governance

Properly organizing data in large organizations is critical. Here are data governance strategies for success in AI and in business.

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Learn more from the first-ever course on Data-Centric AI, taught at MIT by the Cleanlab team and made freely available.

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More resources

Explore applications of Cleanlab Studio via blogs, tutorials, videos, and read the research that powers this next-generation platform.

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Join the Cleanlab Community to ask questions and see how scientists and engineers are practicing Data-Centric AI.