https://github.com/amrrs/automl-kaggle-survey-2019

Carving out the AutoML niche from Kaggle Survey
https://github.com/amrrs/automl-kaggle-survey-2019

2019 automl developer-survey kaggle r rstats

Last synced: 24 days ago
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Carving out the AutoML niche from Kaggle Survey

• Host: GitHub
• URL: https://github.com/amrrs/automl-kaggle-survey-2019
• Owner: amrrs
• Created: 2019-12-07T18:22:43.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2019-12-07T18:38:31.000Z (about 5 years ago)
• Last Synced: 2024-11-15T04:52:06.970Z (3 months ago)
• Topics: 2019, automl, developer-survey, kaggle, r, rstats
• Language: HTML
• Homepage: https://amrrs.github.io/automl-kaggle-survey-2019/automl.html
• Size: 3.84 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        

# AutoML Insights from Kaggle Survey 2019

Companies like Google, H2O, DataRobot are making huge investments with AutoML as their front cover. In fact, they managed to do well on Gartner’s magic quadrant and secure venture funding due the same fact because it sounds revolutionary.

But the real question here is, How receptive the Data science community has been in adopting these AutoML tools? Are they really being used in real life or just being a marketing material? These questions are quite hard to answer at any level.

This notebook tries to leverage a few questions in the Kaggle 2019 Survey to understand the who and what part of AutoML.

Considering AutoML itself a very small niche, I’ve attempted to carve out the niche from this Huge Survey.

### Kaggle Kernel/notebook: - [Carving out the AutoML niche from Kaggle Survey](https://www.kaggle.com/nulldata/carving-out-the-automl-niche-from-kaggle-survey)

### Dataset: [Kaggle Survey 2019](https://www.kaggle.com/c/kaggle-survey-2019)