This repository contains IPython notebooks and other resources from my talk IPython is Great (for large-scale computation, data exploration, and creating reproducible research artifacts). The slides and IPython notebooks from my talk were featured in the 2013 Data Science course at Harvard.
The Keynote file containing my slides is contained in this Github repository. Alternatively you can download my slides as a PDF. All my tutorial code can be browsed online with the IPython Notebook Viewer using the links below.
- Documenting your Research Journey
- Interactively Exploring your Data with Mayavi
- Exploiting Cluster-Level Parallelism
- Using Cython for Extra Performance
- Using Qt from within IPython
If you hit any roadblocks, check out my development environment setup instructions and the official IPython documentation.