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An example Python machine learning notebook for newcomers
- WhatsName 11y agoLink to notebook on IPython Notebook Viewer: http://nbviewer.ipython.org/github/rhiever/Data-Analysis-and-Machine-Learning-Projects/blob/master/example-data-science-notebook/Example%20Machine%20Learning%20Notebook.ipynb http://nbviewer.ipython.org/github/rhiever/Data-Analysis-and...
- misiti3780 11y agoserious question - now that github natively supports ipython is there any reason to link to nbviewer ?
- minimaxir 11y agoThe 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.
- misiti3780 11y agogood to know - thank you!
- rhiever 11y agoThe 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.
- siddboots 11y agoAutomated 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 https://github.com/minrk/ipython_extensions
- rhiever 11y agoVery cool - thank you for pointing me to this!
- bentpins 11y agoIt loaded in about 1/10th the time for me
- flashman 11y agoHey 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.
- rhiever 11y agoCoffee... lots and lots of coffee. :-)
- teekert 11y agoThis 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!!
- rhiever 11y agoHappy to hear it! I partly made this notebook to convert my coworkers and collaborations to a Pythonic workflow, so this is promising... :-)
- teekert 11y agoDefinitely, 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.
- nitin_flanker 11y agoThis is beautiful. Thanks a lot. This is so much resourceful for a person like me who is a rookie.
- kelseydh 11y agoThis 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!
- deleted 11y ago[deleted]