These are all of my notes related to learning how to use python for scientific computing, including scipy, numpy, etc. I will be updating the notebook(s) regularly.
I highly recommend cloning this repository and keeping/modifying/adding you're own notes as well! The magic of IPython is in the notebooks interactive ability! Clone this repository, fire up Ipython and open it in your browser to begin playing around. Add new cells to further clarify examples and make notes for yourself! Feel free to add entire sections for new packages you explore!
Assuming you've already installed Continuum's Anaconda Scientific Python distribution on your windows machine, you can just fire up a command prompt and type:
git clone https://github.com/revolunet/sublimetext-markdown-preview.git
cd scientific-python
ipython notebookYour browser should fire up with the notebook ready for use!
You can also just view the notebook online (not edit/execute) by using the fantastic IPython Notebook Viewer. You can view this specific collection of notebooks by clicking here: Scientific Python.
Or individual lectures at: