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Employee Attrition Dataset and basic structure#99

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gimseng merged 19 commits intogimseng:masterfrom
AjayKhalsa:employee-attrition
Oct 1, 2020
Merged

Employee Attrition Dataset and basic structure#99
gimseng merged 19 commits intogimseng:masterfrom
AjayKhalsa:employee-attrition

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@AjayKhalsa
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@AjayKhalsa AjayKhalsa commented Oct 1, 2020

I'll add more detailed instructions in asap

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gimseng commented Oct 1, 2020

Hi @AjayKhalsa thanks for the contribution. Please add data source/credit in the readme.md either in data or exercise folders (or both). Perhaps once you are done with the first pass of the structures, comment here and we can merge it so others can contribute to this folder.

@AjayKhalsa AjayKhalsa linked an issue Oct 1, 2020 that may be closed by this pull request
@AjayKhalsa
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@gimseng I made a basic structure, check it out. I'm thinking they can add their model's description in the readme provided in the solution folder but what should be its structure? Also, many contributors will make PR's using the same models so would we merge the best model?

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gimseng commented Oct 1, 2020

@AjayKhalsa Could you link or provide documentations on the data in the readme.md of the data folder?

If the data is publicly available online, please provide a link for a detailed description of the data.

If its not public, but it is fine for us to use, please provide a detailed documentations, either uploading them or copied and pasted more detailed descriptions in the readme.md

Sorry to insist on this, but I just want to make sure we won't get into trouble due to privacy concerning data. Furthermore, it is important to understand where the data is from, the quality of data collection and limitations of the data.

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AjayKhalsa commented Oct 1, 2020

@gimseng The dataset was a part of this competition https://www.kaggle.com/c/summeranalytics2020
If it doesn't seem appropriate I can just replace it with the original IBM Employee Dataset which is openly available viz https://www.kaggle.com/pavansubhasht/ibm-hr-analytics-attrition-dataset

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I think for safer side we should just use IBM's dataset, i'll replace it

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gimseng commented Oct 1, 2020

@AjayKhalsa Thanks ! Sure, I'm agnostic of the source, as long as its properly documented somewhere that we can link to and provide credit for. I've cleaned up the exercise and solution readme a bit further. We could merge it as soon as you have finished the data source/credit part of the 'data' folder. Thanks !

@gimseng gimseng mentioned this pull request Oct 1, 2020
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@gimseng I updated the dataset you can merge it now, if we need to make any changes we can do it directly.

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gimseng commented Oct 1, 2020

@AjayKhalsa Great! I shall merge now.

@gimseng gimseng merged commit 8d0223c into gimseng:master Oct 1, 2020
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[IMP] Implement Basic ML Algorithms on a Employee Attrition Dataset

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