https://github.com/nma/awesome-ipython

a collection of IPython notebooks detailing the common mathematical concepts that are required to solve hard problems
https://github.com/nma/awesome-ipython

List: awesome-ipython

Last synced: 3 days ago
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a collection of IPython notebooks detailing the common mathematical concepts that are required to solve hard problems

• Host: GitHub
• URL: https://github.com/nma/awesome-ipython
• Owner: nma
• License: apache-2.0
• Created: 2015-10-28T01:48:14.000Z (about 9 years ago)
• Default Branch: master
• Last Pushed: 2017-01-09T18:53:36.000Z (almost 8 years ago)
• Last Synced: 2024-11-07T18:05:46.096Z (5 days ago)
• Size: 7.81 KB
• Stars: 2
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# awesome-ipython

A selection of IPython notebooks detailing the common mathematical concepts that are required to solve hard problems

the bigger list is found at [IPython](https://github.com/ipython/ipython/wiki/A-gallery-of-interesting-IPython-Notebooks#statistics-machine-learning-and-data-science)

# Mathematics

[Probalistic Programming and Bayesian Methods](https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers)

[Probability](http://nbviewer.jupyter.org/url/norvig.com/ipython/Probability.ipynb)

[Applied Numberical Computation](https://github.com/numerical-mooc/numerical-mooc)

[Monte Carlo Methods, Stochastic Optimization](http://am207.github.io/2016/)

# Finance

[Financial Data Analysis with Ipython and zipline](http://nbviewer.jupyter.org/gist/twiecki/3962843)

[Computational data tools for financial economics](https://github.com/rsvp/fecon235)

# NLP

[Python Programming for the Humanities](http://www.karsdorp.io/python-course/)

[News Categorization using Multinomial Naive Baye](http://nbviewer.jupyter.org/github/andressotov/News-Categorization-MNB/blob/master/News%20Categorization%20MNB.ipynb)

[Mining the Social Web](https://github.com/ptwobrussell/Mining-the-Social-Web-2nd-Edition)

# DeepLearning

[Britefury Deep learning tutorial for PyData London 2016](https://github.com/Britefury/deep-learning-tutorial-pydata2016.git)

# Infrastructure

[Python Big Data Course](https://github.com/phelps-sg/python-bigdata)

# Misc

[Blogging on Octopress with Ipython](http://nbviewer.jupyter.org/github/jakevdp/jakevdp.github.com/blob/master/downloads/notebooks/nb_in_octopress.ipynb)