Data Quality Collection

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📦Normal

★★★★

“Learn how to develop, deploy and iterate on production-grade ML applications.”

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📦Normal

★★★★

“📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.”

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💎Aqua

★★★

“OpenMetadata is a unified metadata platform for data discovery, data observability, and data governance powered by a central metadata repository, in-depth column level lineage, and seamless team collaboration.”

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🔮Psychic

★★★

“1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames. ”

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🔮Psychic

★★★

“Always know what to expect from your data.”

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🔮Psychic

★★★

“Cleanlab's open-source library is the standard data-centric AI package for data quality and machine learning with messy, real-world data and labels.”

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🔮Psychic

★★★

“Refine high-quality datasets and visual AI models”

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📦Normal

★★★

“Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.”

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🔮Psychic

★★★

“The Open Source Feature Store for AI/ML”

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🌊Water

★★★

“lakeFS - Data version control for your data lake | Git for data”

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📦Normal

★★

“Learn how to design, develop, deploy and iterate on production-grade ML applications.”

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🔮Psychic

★★

“Compare tables within or across databases”

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📦Normal

★★

“An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collection, ensuring safety & robustness. 📈”

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🔮Psychic

★★

“Data Contracts engine for the modern data stack. https://www.soda.io”

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🌊Water

★★

“The Virtual Feature Store. Turn your existing data infrastructure into a feature store.”

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🔥Fire

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“Feathr – A scalable, unified data and AI engineering platform for enterprise”

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🔮Psychic

★★

“Scalable data pre processing and curation toolkit for LLMs”

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🔥Flame

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“re_data - fix data issues before your users & CEO would discover them 😊”