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https://github.com/g4brielvs/data-science-playground

Collection of data science and visualization exercises
https://github.com/g4brielvs/data-science-playground

boston-housing-dataset introduction-to-data-science plotly scikit-learn tensorflow

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Collection of data science and visualization exercises

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# data-science-playground

Collection of Data Science and Data Visualization exercises using:

- [Jupyter](http://jupyter.org)
- [NumPy](http://www.numpy.org)
- [SciPy](http://www.scipy.org)
- [pandas](http://pandas.pydata.org)
- [scikit-learn](http://scikit-learn.org/)

and

- [matplotlib](http://matplotlib.org)
- [seaborn](http://seaborn.pydata.org)
- [plotly](https://plot.ly)

## Inspirations

- [An Introduction to Statistical Learning](https://www-bcf.usc.edu/~gareth/ISL/)
- [The Elements of Statistical Learning](https://web.stanford.edu/~hastie/ElemStatLearn/)

## Installation
*data-science-playground* uses `pipenv` to manage dependencies. It works with Python 3.5+.

1. Clone the repository: `$ git clone git@github.com:g4brielvs/data-science-playground.git`.

2. Go to the repository directory: `$ cd data-science-playground` (if you want, get your [virtualenv](https://pypi.python.org/pypi/virtualenv) running there).

4. Install the dependencies: `$ pipenv install`.

## Example

Just run `jupyter notebook` and select a working notebook. For example:

It opens the notebook on the browser of your choice. You can just hit `Run All` to the see the magic. Voilà!

## Contributing

Feel free to [report an issue](https://github.com/g4brielvs/data-science-playground/issues), [open a pull request](https://github.com/g4brielvs/data-science-playground/pulls), or [drop a line](https://g4brielvs.me).

## License
[Creative Commons Attribution-ShareAlike 4.0 International license](http://creativecommons.org/licenses/by-sa/4.0/).
Please feel free to make alterations via pull-request.