This is the page for the afternoon practical sessions of the Large Scale Machine Learning course of Mines ParisTech.

Preparing for the practical sessions

The practical sessions will rely heavily on Python and the following packages: numpy, scipy, matplotlib, seaborn, pandas, scikit-learn, as well as Jupyter notebooks.

Mines students will be using machines of the computer labs (L.117 + L.118). External students should bring their own laptop, with Eduroam already set up (for wireless Internet access).

The easiest way to install all the requirements is to install Anaconda 2 (for Python 2.7).

You can test your installation by downloading one or several of the SciPy 2016 notebooks, starting Anaconda then Jupyter, open the notebook(s) and run them.

You can also install all the above-mentioned Python packages with pip if you already have Python.

Please also download this zip file, which contains the data, notebooks, and documentation you will need for the practical sessions.

Schedule

March 20th 2pm – 5:30pm
Introduction to numpy, pandas, matplotlib, scikit-learn and jupyter with the Titanic data.

March 21st 2pm – 5:30pm
My first RAMP: The Titanic challenge

March 22nd 2pm – 5:30pm
Drug Spectra RAMP: Competitive phase (30% of final grade)

March 23rd 2pm – 5:30pm
Drug Spectra RAMP: Collaborative phase (30% of final grade)

March 24th 2pm – 5:30pm
Drug Spectra RAMP: Competitive phase (40% of final grade)