Tutorial on how to launch Jupyter Notebook in Google GPU cloud.

https://hackernoon.com/launch-a-gpu-backed-google-compute-engine-instance-and-setup-tensorflow-keras-and-jupyter-902369ed5272

#tutorial #jupyter #google

Thomas Wolf’s post on how to make #Python #NLP faster.

Spoiler: use spaCy's internals and a bit of Cython magic

Bonus: a #Jupyter notebook with examples processing over 80 millions words per sec…

https://medium.com/huggingface/100-times-faster-natural-language-processing-in-python-ee32033bdced

How to Create Animated Graphs in Python

Short tutorial on how to create animated graphs, which also works in #jupyter notebooks.

Link: https://towardsdatascience.com/how-to-create-animated-graphs-in-python-bb619cc2dec1
Youtube link with #visualization: https://youtu.be/7xrvuSDLHiY|

#novice #beginner

Top 10 IPython Notebook Tutorials for Data Science and Machine Learning

List mostly for beginners.

Link: https://www.kdnuggets.com/2016/04/top-10-ipython-nb-tutorials.html

#novice #beginner #ipython #jupyter

​​Reproducibility tool for #Jupyter Notebooks

Link: https://mybinder.org

#DS #github #reproducibleresearch

IPython notebooks and git

#IPython or #Jupyter is one of the most popular tools in Data Science. It usage may questionable, but it is optimal for beginners and people who are making thier first steps. This article covers rare theme — keeping notebooks in git repository and optimizing collaboration using them. Main problem lies in technical information (like cell execution count), which is redundant and can be omitted, but still gets written to git in the default scenario.

Link: https://pascalbugnion.net/blog/ipython-notebooks-and-git.html
Code: https://gist.github.com/pbugnion/ea2797393033b54674af

#datascience #practicalML

Nice article on non-official jupyter notebook extensions

Warning: there is a checkbox, saying «disable configuration for nbextensions without explicit compatibility (they may break your notebook environment, but can be useful to show for nbextension development)». So it is better to test the extensions in separate environment.

And correct way to install is extension support is:

pip install jupyter_contrib_nbextensions && jupyter contrib nbextension install --user

Link: https://towardsdatascience.com/setting-up-a-data-science-environment-using-windows-subsystem-for-linux-wsl-c4b390803dd

#jupyter #tipsandtrics

Announcing support for native editing of #jupyter notebooks in #vscode

https://devblogs.microsoft.com/python/announcing-support-for-native-editing-of-jupyter-notebooks-in-vs-code/

Football performance modelling in python

An article with football game outcome analysis in #jupyter.

One of the key features to predict a football game turned out to be the best attacking player even though "A ferocious scream from the stands, a mistaken whistle from the ref’, or the shrimps on the lunch menu may jeopardise the whole outcome of the match."

Authors also highlighted improtance of amplitude of persistence diagrams as a key feature.

This is a suggested by the channel readers material. Don’t forget to thank them by giving claps 👏 on Medium and starring repository if you found a code useful.

Link: https://towardsdatascience.com/the-shape-of-football-games-1589dc4e652a
Code: https://github.com/giotto-ai/football-tda

#football #soccer #betting #readersmaterial

​​An autonomous AI racecar using NVIDIA Jetson Nano

Usually DS means some blue collar work. Rare cases suggest physical interactions. This set by #NVidia allows to build $400/$600 toy car capable of #selfdriving.

#JetRacer comes with a couple examples to get you up and running. The examples are in the format of Jupyter Notebooks, which are interactive documents which combine text, code, and visualization. Once you've completed the notebooks, start tweaking them to create your own racing software!

Github: https://github.com/NVIDIA-AI-IOT/jetracer

#autonomousvehicle #rl #jupyter #physical

☺️526 responses collected thanks to you!

Now we are looking for a volunteer to perform an #exploratory analysis of responses an publish it as a an example on github in a form of #jupyter notebook. If you are familiar with git, jupyter, basics of #exploratory analysis and want to help, write to @opendatasciencebot bot (make sure you include your username, so we can reach you back).

In the mean time, please spend some free weekend time to fill in the questionnaire form if you haven’t filled it yet: https://forms.gle/GGNgukYNQbAZPtmk8 This will help us to make channel better for you.

2020 questionnaire link: https://forms.gle/GGNgukYNQbAZPtmk8

​​Blackcellmagic extension for jupyter

There are people who like dark themes and are fond of them, but this extension helps to format the code.

Extension: https://github.com/csurfer/blackcellmagic
Black formatter: https://github.com/psf/black

#codestyle #python #jupyter

Hands on ML notebook series

Updated our ultimate post with a series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.


Link: https://github.com/ageron/handson-ml

#wheretostart #opensource #jupyter