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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.

Analyzes structured data and helps produce queries, insights or visualizations.

Algorithm capable of fully capturing the impact of data drift on performance.

Distributed, masterless, high performance, fault tolerant data processing. Written entirely in Clojure.

Cleansing, pre-processing, feature engineering, exploratory data analysis and easy ML with PySpark backend.

Pachyderm is a version control system for data.

LLM Comparator is an interactive data visualization tool for evaluating and analyzing LLM responses side-by-side, developed by the PAIR team.

Analyzes structured data and helps produce queries, insights or visualizations.

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media.

A self-organizing data hub with S3 support.

Julia package for loading many of the data sets available in R.

A javascript library containing a collection of least squares fitting methods for finding a trend in a set of data.

Analyzes structured data and helps produce queries, insights or visualizations.

High performance distributed data processing in NodeJS.

A system for quickly generating training data with weak supervision.

Self Organizing Map written in Python (Uses neural networks for data analysis).

Spark is a fast and general engine for large-scale data processing.

Analyzes structured data and helps produce queries, insights or visualizations.

A data exploration platform designed to be visual, intuitive, and interactive.

Workflow tool to automatically organize data visualization output.

A data and concept drift library for PyTorch.

Enriches training datasets with features from public and community shared data sources.

Minimalist neural network library optimized for sparse data and single machine environments.

Cheminfo - Platform for data visualization and analysis, using the project.