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Repeatable, atomic and versioned data lake on top of object storage.
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Published directory entries matching your search.
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Modern columnar data format for ML implemented in Rust.
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Pretrain computer vision models on unlabeled data for industrial applications.
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Collect, aggregate, and visualize a data ecosystem's metadata.
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A tensor-based framework for large-scale data computation which is often regarded as a parallel and distributed version of NumPy.
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Analyzes structured data and helps produce queries, insights or visualizations.
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Algorithm capable of fully capturing the impact of data drift on performance.
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Distributed, masterless, high performance, fault tolerant data processing. Written entirely in Clojure.
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Bring multiple data streams into one dashboard.
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Cleansing, pre-processing, feature engineering, exploratory data analysis and easy ML with PySpark backend.
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Pachyderm is a version control system for data.
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LLM Comparator is an interactive data visualization tool for evaluating and analyzing LLM responses side-by-side, developed by the PAIR team.
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Analyzes structured data and helps produce queries, insights or visualizations.
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Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media.
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A self-organizing data hub with S3 support.
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Julia package for loading many of the data sets available in R.
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A javascript library containing a collection of least squares fitting methods for finding a trend in a set of data.
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Analyzes structured data and helps produce queries, insights or visualizations.
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High performance distributed data processing in NodeJS.
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A system for quickly generating training data with weak supervision.
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Self Organizing Map written in Python (Uses neural networks for data analysis).
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Spark is a fast and general engine for large-scale data processing.
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Analyzes structured data and helps produce queries, insights or visualizations.
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A data exploration platform designed to be visual, intuitive, and interactive.