ISLR
jupytext
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ISLR
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An Introduction to Statistical Learning with Applications in Python
It’s a well known machine learning book. I’ve read through it and done the exercises in R.
https://github.com/melling/ISLR
There’s an edX course from the authors:
https://www.edx.org/course/statistical-learning
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Introduction to statistical learning, 2nd edition
Looks like a few new chapters. e.g Deep Learning
I own the first edition. Made it through the entire book during the pandemic with a study partner.
There are other resources:
https://github.com/melling/ISLR
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R Markdown: The Definitive Guide
I recently discovered R Markdown. Started doing the ISLR examples with it.
https://github.com/melling/ISLR/blob/main/chapter08/08_Lab02...
https://github.com/melling/ISLR/blob/main/chapter08/08_Lab02...
I need to figure out how to better fit images so I don’t have pages with large gaps
Also, you can now embed executable Python in the files.
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The Elements of Statistical Learning [pdf]
I’m up to Chapter 6 in ISLR
https://github.com/melling/ISLR
Would Elements of Statistical Learning be my next book? I’ve seen the Bishop book highly recommended too.
https://www.amazon.com/Pattern-Recognition-Learning-Informat...
jupytext
- The Jupyter+Git problem is now solved
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Do you git commit jupyter notebooks?
Jupytext (https://github.com/mwouts/jupytext) has been designed exactly for this
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The hatred towards jupyter notebooks
jupytext is your friend.
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Edit notebooks in Google cloud
So if you run your own jupyter server, -jupy+text can be a great workflow : it takes your notebook synchronized with other formats (python file, makdown, ...), so you can edit your py/md file with neovim, and refresh the browser to execute the notebook.
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Rant: Jupyter notebooks are trash.
Automatically convert ipynb files to py when saving them on JupyterLab
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Two questions regarding working with jupyter notebooks (git, vim)
I don't use Jupyter so I don't know for sure, but on a quick glance you might want to look at https://github.com/mwouts/jupytext to see if that could help at all.
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JupyterLite is a JupyterLab distribution that runs in the browser
The format is only partially invented, it follows Jupytext [0], but adds support for cell metadata. There is no obvious way to get that in fenced codeblocks, especially with the ability to spread it over multiple lines so it plays well with version control.
One more consideration is that it's not "Markdown with code blocks interspersed", one might as well use plaintext or AsciiDoc.
Of course there are tradeoffs.. I wish I had more time to work on it.
[0]: https://github.com/gzuidhof/starboard-notebook/blob/master/d...
[1]: https://github.com/mwouts/jupytext
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Many write research papers in R Markdown - What is the alternative setup in Python?
Using jupytext (allows you to open .md files as notebooks) + jupyter gives you pretty much the same experience. The main issue is that the cell's output will be discarded. To fix it, you can use ploomber to generate an output HTML, so the workflow goes like this:
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Jupyter Notebooks.
First, the format. The ipynb format does not play nicely with git since it stores the cell's source code and output in the same file. But Jupyter has built-in mechanisms to allow other formats to look like notebooks. For example, here's a library that allows you to store notebooks on a postgres database (I know this isn't practical, but it's a great example). To give more practical advice, jupytext allows you to open .py files as notebooks. So you can develop interactively but in the backend, you're storing .py files.
What are some alternatives?
the-elements-of-statistical-learning - My notes and codes (jupyter notebooks) for the "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani and Jerome Friedman
jupyter - An interface to communicate with Jupyter kernels.
Neptune.jl - Simple (Pluto-based) non-reactive notebooks for Julia
rmarkdown - Dynamic Documents for R
Pluto.jl - 🎈 Simple reactive notebooks for Julia
sagemaker-run-notebook - Tools to run Jupyter notebooks as jobs in Amazon SageMaker - ad hoc, on a schedule, or in response to events
here_here - I love the here package. Here's why.
nbdev - Create delightful software with Jupyter Notebooks
papermill - 📚 Parameterize, execute, and analyze notebooks
StatsWithJuliaBook
nbdime - Tools for diffing and merging of Jupyter notebooks.