Create, visualize, run & benchmark DVC pipelines in Python & Jupyter notebooks.
-
Updated
Feb 20, 2025 - Python
Create, visualize, run & benchmark DVC pipelines in Python & Jupyter notebooks.
A visualization tool for analyzing the reproducibility of Jupyter Notebooks
Automated Quantum Mechanical Environments (AQME) offers transparent and reproducible workflows available for Jupyter Notebooks and command lines, including: 1) RDKit- and CREST-based conformer generation, 2) QM input file creation, 3) post-processing of QM output files, 4) generation of xTB, DFT and RDKit descriptors. https://aqme.readthedocs.io
This repository demonstrates the "Ten Simple Rules for Reproducible Research in Jupyter Notebook" rules for a simple machine learning problem
Reproduce Jupyter Notebooks inside Docker Containers.
"scorecal - Empirical score calibration under the microscope" presentation given at Credit Scoring & Credit Control XVI, Edinburgh, UK, 2019-08-30
🔬 R package: Analysis of Large Affymetrix Microarray Data Sets
Interactive ML Toolset
Reproducible Python notebooks: Using satellite imagery to analyse dynamics of urban neighbourhood.
Generate Powerpoint presentations from Jupyter Notebook results
An example project that uses a Jupyter notebook as a pipeline.
A reproducibility study using the Colomoto notebook
Reproducibilidad en notebooks de google - Python y R
FAIR Jupyter: a knowledge graph for semantic sharing and granular exploration of a computational notebook reproducibility dataset.
Configures Anaconda on Windows and associates double-click on .ipynb files with JupyterLab. To get version controlled Jupyter notebooks, it installs an extension to commit changes directly from JupyterLab, no command-line interaction necessary. |> https://bamresearch.github.io/jupyter-integration |> https://www.youtube.com/channel/UC0Jlyc60Nxc7F…
End to end artifact store (data, scripts, plots, models, notebooks) for the short paper titled "Leveraging human-in-the-loop ML models to learn representations of reproducible articles"
Taking advantage of the open sciene approach of the ATLAS Open Data project and it's tools, for educational purposes, which allow to have an idea of how they perform data analysis in high-energy physics, the project was focused on the automation of the notebooks where these analyzes are carried out and the documentation was expanded to make them…
Add a description, image, and links to the reproducibility topic page so that developers can more easily learn about it.
To associate your repository with the reproducibility topic, visit your repo's landing page and select "manage topics."