The python notebooks in this repo are for the workshops I held on machine learning during Fall Quarter 2016 at UCLA for ACM'S AI club. It is an introduction to machine learning with scikit-learn and python. Currently, workshop one is up, which was help on October 12, 2015.
In order to run the ipython notebook, just follow the steps below
git clone https://github.com/abcde13/MachineLearningWrkshp.git
cd MachineLearningWrkshp.git
ipython notebook
If ipython doesn't work, first see if you have python installed by doing python --version. If you see command not found: python then you need to install it.
Follow this link to install it: http://ipython.org/install.html. However, if you have pip installed (check via the same process as above), I recommend doing
pip install ipython[notebook] ipython[qtconsole]
after running pip intall ipython.
If you don't have anything installed, or you want to use Anaconda because you like the way it sounds, then follow the instructions in the link above to download it. Then, run
conda update conda
conda update ipython ipython-notebook ipython-qtconsole
This should give you all the necessary tools to start using the notebook.
If you truly want to used the notebook the way I gave the presenation, try running this:
ipython nbconvert --to slides --post serve title-of-the-notebook.ipynb
where title-of-the-notebook is one of the ipython notebooks above, such as Intro\ to\ Machine\ Learning or Unsupervised\ Learning
This uses nbconvert to turn the notebook into a presenation via Reveal.js, and a server is then spun up to view the presentation.
Once you've got the presentation up, you can code the examples used by running ipython qtconsole. The qtconsole is necessary because provides a GUI with which to plot things on.
Clicking on th .ipynb file also renders it fully, if you just want to view the entire presenation passively.