LSMLSDA exercises and mini-projects

This repository belongs to the Large Scale Modelling and Large Scale Data Analysis course at TUM: moodle link.

Usage and contribtion

You find exercises in the exercises folder, and mini-projects in the mini-projects folder.

Contribution workflow

All students can push to this repository. This requires that everyone adapts a certain workflow in order to avoid conflicts.

When adding code to this repository, create a local branch first. The name of the branch should be your group name or, if it is for a different assignment, a unique and desciptive name. Push the local branch to the remote and then make a pull request to merge it into the master branch.

Add code exclusively to the your-code folder: create a folder with your group name, e.g., group1, in the your-code folder and work exclusively in this folder.

Setup

We recommend to use conda environments for managing your Python packages. To create a conda environment named lsmlsda execute

conda create --name lsmlsda python=3.5.6

Activate your newly create conda env with source activate lsmlsda. Then install additional packages with

conda install -c anaconda notebook numpy scipy matplotlib pandas.