Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
- data-analysis
- pandas
- flexible
- alignment
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Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.
- ipython
- jupyter
- data-science
- python
Clean APIs for data cleaning. Python implementation of R package Janitor
- pandas
- dataframe
- data
- cleaning-data
Code for PaperRobot: Incremental Draft Generation of Scientific Ideas
- pytorch
- memory-networks
- generation
- end-to-end-learning
[IROS 2020] se(3)-TrackNet: Data-driven 6D Pose Tracking by Calibrating Image Residuals in Synthetic Domains
- robotics
- tracking
- computer-vision
- pose-estimation
A python package for animating plots build on matplotlib.
- plotting
- animation
- data-visualization
- python
Kaapana is an open source toolkit for state of the art platform provisioning in the field of medical data analysis. The applications comprise AI-based workflows and federated learning scenarios with a focus on radiological and radiotherapeutic imaging. The name Kaapana comes from the Hawaiian word kaʻāpana, meaning "distributor" or "part".
- imaging
- ai
- cloud-computing
- medical-imaging
manim cell magic for IPython/Jupyter to show the output video
- jupyter-magic
- jupyer
- manim
- ipython-magic
ChemML is a machine learning and informatics program suite for the chemical and materials sciences.
- quantum-mechanics
- materials-informatics
- data-science
- machine-learning
This project presents a Python-based spam detector program that utilizes the Naive Bayes approach to classify emails as either spam or ham. The system is designed to accurately and efficiently identify spam messages, providing a useful tool for individuals and organizations seeking to manage their email inboxes more effectively.
- anaconda
- jupyter-notebook
- python
A lightweight Python package for teaching computational methods through art history. Extract and analyze artist-specific works from WikiArt with built-in visualizations. Designed for digital humanities and computational design courses. Features genre/style analysis, matplotlib integration, and pedagogical clarity over algorithmic complexity.
- art-history
- color-analysis
- color-extraction
- color-palette
Store,Version and Run jupyter notebook via ReST api