A beautiful graphing toolkit for Ruby.
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A python visualization library based on matplotlib.
A JavaScript library aimed at visualizing graphs of thousands of nodes and edges.
High performance distributed data processing in NodeJS.
Skills supports software development with code generation, analysis, debugging, or documentation.
Analyzes structured data and helps produce queries, insights or visualizations.
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.
Apache Spark is a multi-language engine for executing data engineering, data science, and machine learning on single-node machines or clusters.
Spark is a fast and general engine for large-scale data processing.
Analyzes structured data and helps produce queries, insights or visualizations.
A blog with resources for data science learners.
Statistical modelling and econometrics in Python.
Streaming MapReduce with Scalding and Storm.
The SuperDataScience podcast with Jon Krohn airs the most important topics on machine learning, AI, and data careers. Unleash your data skills.
Supermaven supports software development with code generation, analysis, debugging, or documentation.
A data exploration platform designed to be visual, intuitive, and interactive.
Modern, enterprise-ready business intelligence web application.
The Go Language library for SVG generation.
SWEBench supports software development with code generation, analysis, debugging, or documentation.
A Python library for symbolic mathematics.
Synthetic tabular data generation using GANs, Diffusion Models, and LLMs with adversarial filtering and privacy metrics.
Workflow tool to automatically organize data visualization output.