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selva86

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Build MCMC from Scratch in R: The 50-Line Algorithm Behind Brms and Stan

r-statistics.co
2 points·by selva86·2 bulan yang lalu·0 comments

Object Oriented Programming (OOP) in R Explained

r-statistics.co
1 points·by selva86·3 bulan yang lalu·0 comments

[untitled]

1 points·by selva86·4 bulan yang lalu·0 comments

[untitled]

1 points·by selva86·4 bulan yang lalu·0 comments

Pandas Exercises for Data Analysis (Interactive)

machinelearningplus.com
126 points·by selva86·4 bulan yang lalu·33 comments

The Python Book = Interactive Python Tutorial from Basic to Expert

pythoncompiler.io
3 points·by selva86·5 bulan yang lalu·2 comments

Online Python Compiler – IDE, notebook, editor (no login local)

pythoncompiler.io
1 points·by selva86·6 bulan yang lalu·2 comments

comments

selva86
·3 bulan yang lalu·discuss
[dead]
selva86
·4 bulan yang lalu·discuss
Learn Python by writing Python - Interactive tutorials, no login
selva86
·4 bulan yang lalu·discuss
Made this as well for polars: https://machinelearningplus.com/python/101-polars-exercises-...

I was thinking about it for quite a while, but not sure if there would be interest. Thanks for your comment!
selva86
·4 bulan yang lalu·discuss
Build this as an interactive tool for our popular 101 Pandas exercises. The code runs entirely in local in your browser. Would love feedback on the ease of use and the editor UX.
selva86
·5 bulan yang lalu·discuss
This will be a helpful resource for those who prefer to learn via books and blog, but also want to practice what they learn in the same page. So, this is like a blog but is also a fully functional Python notebook which you can use to workout python code and also solve exercises. It's meant to be comprehensive starting from the very basic to advanced Python concepts that's not often discussed in classrooms, in one sequential flow of lessons. I hope you enjoy it!
selva86
·6 bulan yang lalu·discuss
Introducing a new featureful online compiler.

Your code automatically saves every 2 seconds. Install more packages, create or upload existing Jupyter notebooks to continue working on them, your code runs completely local in browser - nothing is sent to servers.