Automatically visualize your pandas dataframe via a single print! 📊 💡

An easy to use blogging platform, with enhanced support for Jupyter Notebooks.

fastdup is a powerful, free tool designed to rapidly generate valuable insights from image and video datasets. It helps enhance the quality of both images and labels, while significantly reducing data operation costs, all with unmatched scalability.

Vue 界面可视化设计器，支持任何 html 标签以及项目中引用的组件，可实现仅通过配置文件就能增加支持的组件和组件属性

zzllrr mather(an offline tool for Math learning, education and research)小乐数学，离线可用的数学学习（自学或教学）、研究辅助工具。计划覆盖数学全部学科的解题、作图、演示、探索工具箱。目前是演示Demo版（抛转引玉），但已经支持数学公式编辑显示，部分作图功能，部分学科，如线性代数、离散数学的部分解题功能。最终目标是推动专业数学家、编程专家、教育工作者、科普工作者共同打造出更加专业级的Mather数学工具

ACTS is a white box testing framework based on data model drivers.

Deep Replay - Generate visualizations as in my "Hyper-parameters in Action!" series!

An awesome repository & A comprehensive survey on interpretability of LLM attention heads.

A very fast visualization library for large, high-dimensional data sets.

Complex Analysis: A Visual and Interactive Introduction

Yet Another Compiler Visualizer

Interactive details-on-demand data visualizations at scale

Interactive document creation for exploratory graphics and visualizations. 咲いて (in bloom). Built on top of hanami vega/vega-lite library with CodeMirror and self hosted ClojureScript

PyTorch Implementation of GraphTSNE, ICLR’19

Visualizing query-key interactions in language + vision transformers

GenoVi, an automated customizable circular genome visualizer for bacteria and archaea

Flexible Statistics and Data Analysis (FSDA) extends MATLAB for a robust analysis of data sets affected by different sources of heterogeneity. It is open source software licensed under the European Union Public Licence (EUPL). FSDA is a joint project by the University of Parma and the Joint Research Centre of the European Commission.

This is a repo that investigates or develops tools to make work easier and enjoyable, especially for research stuffs

The official PyTorch implementation - Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective (CVPR'22).

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