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# Data Mining and Exploration
###### Original 2017 version by Agamemnon Krasoulis
This repository contains the code for the [University of Edinburgh](http://www.ed.ac.uk/) [School of Informatics](http://www.ed.ac.uk/informatics/) course Data Mining and Exploration [INFR11007].
## Links
  * [School course page](http://www.inf.ed.ac.uk/teaching/courses/dme/)
  * [University course page](http://www.drps.ed.ac.uk/17-18/dpt/cxinfr11007.htm)
  * [GitHub page (Labs)](https://github.com/sinziana91/DME)

## Labs general information

In this course we will be using Python 3 and the interactive notebook application [Jupyter](http://jupyter.readthedocs.io/) for all labs. Basic knowledge of `python`, `numpy` and working with `notebooks` in the Jupyter environment is assumed for this course. If you haven't used python before, you are strongly advised to familiarise yourself with basic python syntax and working in the Jupyter environment. There are many excellent tutorials available on the web and you can choose the ones you like the most. If you are not sure which ones to choose, these are good starting points:

[Introduction to Python for scientific computing](http://bebi103.caltech.edu/2015/tutorials/t1a_intro_to_python.html)

[Introduction to Jupyter notebooks](http://bebi103.caltech.edu/2015/tutorials/t0b_intro_to_jupyter_notebooks.html)

[Python/Numpy tutorial](http://cs231n.github.io/python-numpy-tutorial/#python)

## Packages

The main **packages** that we will use are the following:
* [numpy:](http://www.numpy.org/) scientific computing by using array objects

* [pandas](http://pandas.pydata.org/): data structures and data analysis tools

* [scikit-learn](http://scikit-learn.org/stable/): machine learning library implementing many learning algorithms and useful tools

* [matplotlib](http://matplotlib.org/): plotting library (similar to MATLAB's plot interface)

* [seaborn](https://seaborn.github.io/index.html): data visualisation library which works on top of matplotlib

## Getting set up
  Detailed instructions for setting up a development environment for the course are given in [this file](https://github.com/sinziana91/DME/blob/master/environment-set-up.md).

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