This is beautiful. Thanks a lot. This is so much resourceful for a person like me who is a rookie.
An example Python machine learning notebook for newcomers
11–17 of 17 posts
Re: An example Python machine learning notebook for newcomers
#12This 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!
Re: An example Python machine learning notebook for newcomers
#13[deleted]
Re: An example Python machine learning notebook for newcomers
#14Earlier quoted context omitted.
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!
Re: An example Python machine learning notebook for newcomers
#15This 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: N…
Happy to hear it! I partly made this notebook to convert my coworkers and collaborations to a Pythonic workflow, so this is promising... :-)
Re: An example Python machine learning notebook for newcomers
#16Hey 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. :-)
Re: An example Python machine learning notebook for newcomers
#17This 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: N…
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.