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https://github.com/rahul-404/hr-analytics


https://github.com/rahul-404/hr-analytics

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# HR-Analytics

HR-Analytics, Here is an opportunity to try predictive analytics in identifying the employees most likely to get promoted.
[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://drive.google.com/drive/folders/1ckdpw-I_b3VOUK93AFk2IFfA6b4nBtuq?usp=sharing)

## Dataset:

This [dataset](https://datahack.analyticsvidhya.com/contest/wns-analytics-hackathon-2018-1/) is from Hackathon organized by Analytics Vidhya platform

## Description:

- This is a machine learning classification project from the domain of HR analytics.
- It achieved 52.67% of accuracy with ensembled model.
- Benchmarked at [48th rank](https://github.com/Rahul-404/HR-Analytics/blob/main/Leader_Board/Rank_48.png) among 13532 other participants.

## Code Requirements:

python 3.x with following modules installed

[Jupyter Notebook](https://jupyter.org/) - Jupyter is a free, open-source, interactive web tool known as a computational notebook

or

[notebook](https://pypi.org/project/notebook/)

## Installation & Execution:

[How to install Jupyter Notebook](https://www.geeksforgeeks.org/how-to-install-jupyter-notebook-in-windows/)

## Built With
* [Python](https://www.python.org/) - High-level programming language

## Purpose
The purpose of this project was to gain introductory exposure to Machine Learning Classification concepts. The project makes heavy use of [Pandas](https://pandas.pydata.org/), [Numpy](https://numpy.org/), [Matplotlib](https://matplotlib.org/), [Seaborn](https://seaborn.pydata.org/), [Sklearn](https://scikit-learn.org/stable/)

## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

Please make sure to update tests as appropriate.

## License

[MIT](https://github.com/Rahul-404/HR-Analytics/blob/main/LICENSE)