An example Python machine learning notebook for newcomers | Hacker News Reader

An example Python machine learning notebook for newcomers

github.com

174 pointsrhiever15 comments

Link to notebook on IPython Notebook Viewer: http://nbviewer.ipython.org/github/rhiever/Data-Analysis-and...

serious question - now that github natively supports ipython is there any reason to link to nbviewer ?

The GitHub rendering engine for Ipython notebooks does not support mobile devices (oddly) and it does not support custom CSS/plugins, although this notebook does not utilize any of the latter.

good to know - thank you!

The native GitHub IPython Notebook viewer also doesn't support within-notebook linking, which can be fairly annoying when you spend an hour putting together a nice table of contents system.

Automated table of contents really should be built into Jupyter, given how often it is used in practice. Although there is an nbextension [1].

[1] https://github.com/minrk/ipython_extensions

Very cool - thank you for pointing me to this!

It loaded in about 1/10th the time for me

Hey Randy, just wanted to say thanks for doing so much to help others extend their knowledge of data science. I don't know where you get your energy but it's been fun watching your rising profile in the data scientist community.

Coffee... lots and lots of coffee. :-)

This is great! I have been using iPython notebook (as a biologist) for some months now and "getting a feel for the data" is very important. This notebook is littered with handy Python one liners to quickly gain insight into the data.

I love iPython notebook, I can run the entire back-end on our cluster while working with terabytes of data on my laptop tethered to my phone from a moving train (as we speak ;)).

Edit: Now using your code directly on my own data, I'm learning a lot, a big thanks to Randal S. Olson!!

Happy to hear it! I partly made this notebook to convert my coworkers and collaborations to a Pythonic workflow, so this is promising... :-)

Definitely, to me the whole cleaning up of data while leaving the code as a trace of that you did is an eye opener (I'm a real noob). iPython notebook is ideal for this. I just started using markdown field to write in a detailed way what I'm exactly doing. I bet it will be helpful to other currently Python unaware colleagues.

This is one of those few tutorials where you truly learn more from just reading through it than you do from seeing the code. Excellent material!

This is beautiful. Thanks a lot. This is so much resourceful for a person like me who is a rookie.

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