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https://github.com/Azure/Azure-TDSP-Utilities
Utilities and scripts developed as part of Microsoft's Team Data Science Process for productive data science
https://github.com/Azure/Azure-TDSP-Utilities
Last synced: 10 days ago
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Utilities and scripts developed as part of Microsoft's Team Data Science Process for productive data science
- Host: GitHub
- URL: https://github.com/Azure/Azure-TDSP-Utilities
- Owner: Azure
- License: cc-by-4.0
- Archived: true
- Created: 2016-09-09T20:42:17.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2018-11-08T22:01:21.000Z (over 5 years ago)
- Last Synced: 2024-04-02T15:18:17.129Z (about 2 months ago)
- Language: HTML
- Homepage:
- Size: 14.4 MB
- Stars: 371
- Watchers: 152
- Forks: 272
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
- License: LICENSE-CODE.TXT
Lists
- AI - TDSP-Utilities - Two data science utilities in R from Microsoft: 1) Interactive Data Exploration, Analysis, and Reporting (IDEAR) ; 2) Automated Modeling and Reporting (AMR). (R / General-Purpose Machine Learning)
- awesome-machine-learning - TDSP-Utilities - Two data science utilities in R from Microsoft: 1) Interactive Data Exploration, Analysis, and Reporting (IDEAR) ; 2) Automated Modelling and Reporting (AMR). (R / General-Purpose Machine Learning)
- jimsghstars - Azure/Azure-TDSP-Utilities - Utilities and scripts developed as part of Microsoft's Team Data Science Process for productive data science (HTML)
- jimsghstars - Azure/Azure-TDSP-Utilities - Utilities and scripts developed as part of Microsoft's Team Data Science Process for productive data science (HTML)
- jimsghstars - Azure/Azure-TDSP-Utilities - Utilities and scripts developed as part of Microsoft's Team Data Science Process for productive data science (HTML)
- awesome-machine-learning - TDSP-Utilities - Two data science utilities in R from Microsoft: 1) Interactive Data Exploration, Analysis, and Reporting (IDEAR) ; 2) Automated Modeling and Reporting (AMR). (R / General-Purpose Machine Learning)
- awesome-machine-learning - TDSP-Utilities - Two data science utilities in R from Microsoft: 1) Interactive Data Exploration, Analysis, and Reporting (IDEAR) ; 2) Automated Modelling and Reporting (AMR). (R / General-Purpose Machine Learning)
- awesome-machine-learning - TDSP-Utilities - Two data science utilities in R from Microsoft: 1) Interactive Data Exploration, Analysis, and Reporting (IDEAR) ; 2) Automated Modeling and Reporting (AMR). (R / General-Purpose Machine Learning)
- awesome-machine-learnings - TDSP-Utilities - Two data science utilities in R from Microsoft: 1) Interactive Data Exploration, Analysis, and Reporting (IDEAR) ; 2) Automated Modeling and Reporting (AMR). (R / General-Purpose Machine Learning)
- awesome-machine-learning-library - TDSP-Utilities - Two data science utilities in R from Microsoft: 1) Interactive Data Exploration, Analysis, and Reporting (IDEAR) ; 2) Automated Modeling and Reporting (AMR). (R / General-Purpose Machine Learning)
- awesome-machine-learning - TDSP-Utilities - Two data science utilities in R from Microsoft: 1) Interactive Data Exploration, Analysis, and Reporting (IDEAR) ; 2) Automated Modeling and Reporting (AMR). (R / General-Purpose Machine Learning)
- awesome-machine-learning - TDSP-Utilities - Two data science utilities in R from Microsoft: 1) Interactive Data Exploration, Analysis, and Reporting (IDEAR) ; 2) Automated Modelling and Reporting (AMR). (R / General-Purpose Machine Learning)
- awesome-machine-learning - TDSP-Utilities - Two data science utilities in R from Microsoft: 1) Interactive Data Exploration, Analysis, and Reporting (IDEAR) ; 2) Automated Modeling and Reporting (AMR). (R / General-Purpose Machine Learning)
- awesome-machine-learning - TDSP-Utilities - Two data science utilities in R from Microsoft: 1) Interactive Data Exploration, Analysis, and Reporting (IDEAR) ; 2) Automated Modelling and Reporting (AMR). (R / General-Purpose Machine Learning)
- awesome-machine-learning - TDSP-Utilities - Two data science utilities in R from Microsoft: 1) Interactive Data Exploration, Analysis, and Reporting (IDEAR) ; 2) Automated Modeling and Reporting (AMR). (R / General-Purpose Machine Learning)
- awesome-machine-learning - TDSP-Utilities - Two data science utilities in R from Microsoft: 1) Interactive Data Exploration, Analysis, and Reporting (IDEAR) ; 2) Automated Modeling and Reporting (AMR). (R / General-Purpose Machine Learning)
- awesome-machine-learning - TDSP-Utilities - Two data science utilities in R from Microsoft: 1) Interactive Data Exploration, Analysis, and Reporting (IDEAR) ; 2) Automated Modeling and Reporting (AMR). (R / General-Purpose Machine Learning)
- awesome-machine-learning - TDSP-Utilities - Two data science utilities in R from Microsoft: 1) Interactive Data Exploration, Analysis, and Reporting (IDEAR) ; 2) Automated Modeling and Reporting (AMR). (R / General-Purpose Machine Learning)
- awesome-machine-learning - TDSP-Utilities - Two data science utilities in R from Microsoft: 1) Interactive Data Exploration, Analysis, and Reporting (IDEAR) ; 2) Automated Modeling and Reporting (AMR). (R / General-Purpose Machine Learning)
- awesome-machine-learning - TDSP-Utilities - Two data science utilities in R from Microsoft: 1) Interactive Data Exploration, Analysis, and Reporting (IDEAR) ; 2) Automated Modeling and Reporting (AMR). (R / General-Purpose Machine Learning)
- awesome-machine-learning - TDSP-Utilities - Two data science utilities in R from Microsoft: 1) Interactive Data Exploration, Analysis, and Reporting (IDEAR) ; 2) Automated Modeling and Reporting (AMR). (R / General-Purpose Machine Learning)
- my-awesome-stars - Azure/Azure-TDSP-Utilities - Utilities and scripts developed as part of Microsoft's Team Data Science Process for productive data science (HTML)
README
# Data Science Utilities from Microsoft
[**Interactive Data Exploration, Analysis, and Reporting**](DataScienceUtilities/DataReport-Utils/) | [**Automated Modeling and Reporting**](DataScienceUtilities/Modeling/) | [**TDSP**](https://docs.microsoft.com/en-us/azure/machine-learning/team-data-science-process/overview)
This repository contains a set of **Data Science Utilities** developed for use in the context of the [Team Data Science Process (TDSP)](https://docs.microsoft.com/en-us/azure/machine-learning/team-data-science-process/overview).
## Release Notes
This is an **early preview** release of the Data Science Utilities for TDSP. We are continuously improving our data science utilities based on our further accumulated experience and customer requests. Stay tuned for future releases.
Currently, the Data Science Utilities released in this repository include:
- [Interactive Data Exploration, Analysis, and Reporting (IDEAR) in R](DataScienceUtilities/DataReport-Utils/R).
- [Interactive Data Exploration, Analysis, and Reporting (IDEAR) in MRS](DataScienceUtilities/DataReport-Utils/MRS).
- [Interactive Data Exploration, Analysis, and Reporting (IDEAR) in Python](DataScienceUtilities/DataReport-Utils/Python).
- [Automated Modeling and Reporting in R (AMAR in R)](DataScienceUtilities/Modeling/)
You can easily run these utilities on sample data in the **Data/Common** directory. If you are using [Azure Data Science Virtual Machine](https://azure.microsoft.com/en-us/marketplace/partners/microsoft-ads/standard-data-science-vm/), all three utilities are instantly ready to run.
## Ask Questions.
We would love to hear back from you. Should you have any questions or suggestions, or you want to report a bug, please create issues at [TDSP/Issues](https://github.com/Azure/Azure-TDSP-Utilities/issues)
## Help to Enrich the Set of Utilities
We believe that with the help of the data science community, the set of data science utilities can be significantly enriched and can become more powerful, and can benefit more enterprises and more data scientists. We warmly welcome you to contribute to the data science utilities for TDSP.
## What Is TDSP
To know more details about TDSP, check out the TDSP documents [here](https://aka.ms/tdsp).
## Additional notes
In documentations, Screenshots of [RStudio](https://www.rstudio.com/) are from the Open Source Edition.