fitrialif/big-data-tutorial-1

Big Data Tutorial

Big Data lectures as IPython notebooks

Those are lectures and demonstrations of BigData using several libraries such as pandas, scikit-learn, mrjob and ipython.

The target audience is experienced Python developers familiar with scientific computing.

Source code of the tutorial and exercises

To open these notebooks in IPython, download the files to a directory on your computer and from that directory run:

$ ipython notebook

This will open a new page in your browser with a list of the available notebooks.

Online read-only versions

Use the following links:

• [0-Introduction-to-Pandas](http://nbviewer.ipython.org/urls/raw.github.com/marcelcaraciolo/big-data-tutorial/master/tutorial/0-Introduction-to-Pandas.ipynb)
• [1-Playing-with-recommender-systems](http://nbviewer.ipython.org/urls/raw.github.com/marcelcaraciolo/big-data-tutorial/master/tutorial/1-Playing-with-Recommender-Systems.ipynb)
• [2-Introduction-to-Scikit-Learn](http://nbviewer.ipython.org/urls/raw.github.com/marcelcaraciolo/big-data-tutorial/master/tutorial/2-Introduction-to-Scikit-Learn.ipynb)
• [3-Map-Reduce](http://nbviewer.ipython.org/urls/raw.github.com/marcelcaraciolo/big-data-tutorial/master/tutorial/3-Map-Reduce.ipynb)

License

This tutorial is distributed under the Creative Commons Attribution 3.0 license. The Python example code and solutions to exercises are distributed under the license Simplified BSD.