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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.

Basic sampling algorithms for Julia.

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

A beautiful graphing toolkit for Ruby.

High performance distributed data processing in NodeJS.

A system for quickly generating training data with weak supervision.

AI-generated visualization prototyping and editing platform, support 2D, 3D models, combined with LLM(Large Language Model) for quick editing.

Massively parallel self-organizing maps: accelerate training on multicore CPUs, GPUs, and clusters, has python API.

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.

Statistical modelling and econometrics in Python.

Streaming MapReduce with Scalding and Storm.

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

The Go Language library for SVG generation.

A Python library for symbolic mathematics.

Scripts to load several popular datasets including:.

A data and concept drift library for PyTorch.

Interactive notebook-based tool to visualize the forward pass of any PyTorch model.

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

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

A Python Framework for Wind Energy Analysis and Prediction.

AI evaluation platform for interactively exploring data and model outputs.