Skip to content

This repository includes the codes for the PyData talk Eindhoven 2020: The industrial challenge of missing data

License

Notifications You must be signed in to change notification settings

bezhvin/PyData2020-Eindhoven

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

19 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

PyData2020-Eindhoven

This repository includes the codes for the my talk at PyData Eindhoven 2020: The industrial challenge of missing data. The talk is available on YouTube, and the slides are here.

Description

Two practical notebooks ready to run in colab are available to practice missing data imputation.

The notebook "PyData_missingdata.ipynb" includes some imputation examples as shown and explained in the talk. It may get extended with new methodologies, stay tuned!

The notebook "PyData_GAIN.ipynb" is the implementation of GAIN with kersa and Tensorflow 2.x. Noting that another different implementation of this is available here

Useful links:

[Sklearn.impute] (https://scikit-learn.org/stable/modules/impute.html)

[fancyimpute] (https://github.com/iskandr/fancyimpute)

About

This repository includes the codes for the PyData talk Eindhoven 2020: The industrial challenge of missing data

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published