💎 Slides from Clauset's "Introduction to Networks" lecture at #SICSS2018, a super quick tour of some basic network science concepts and methods + application of them to understand faculty hiring networks in academia
https://t.co/D9iJ7aaVD2
https://t.co/D9iJ7aaVD2
☑ Parallel Programming with Python
https://chryswoods.com/parallel_python/index.html
https://chryswoods.com/parallel_python/index.html
🔥 Set of illustrated Machine Learning cheat sheets from Stanford's CS 229 class:
Deep Learning: https://t.co/BNQ7FpUum4
Supervised Learning: https://t.co/5bhzGHlUCl
Unsupervised Learning: https://t.co/ZaD94OQNNN
Tips and tricks: https://t.co/SciByei6a1
Deep Learning: https://t.co/BNQ7FpUum4
Supervised Learning: https://t.co/5bhzGHlUCl
Unsupervised Learning: https://t.co/ZaD94OQNNN
Tips and tricks: https://t.co/SciByei6a1
stanford.edu
CS 229 - Deep Learning Cheatsheet
Teaching page of Shervine Amidi, Graduate Student at Stanford University.
🔥 A full trannoscript of the tutorial with jupyter notebooks, data, slides, etc. is now available at
https://ingoscholtes.github.io/kdd2018-tutorial/
https://ingoscholtes.github.io/kdd2018-tutorial/
Beyond Graph Mining - Higher-Order Data Analytics for Temporal Network Data
KDD 2018 - Hands-on Tutorial on Higher-Order Data Analytics
Companion website for KDD’18 Hands-On Tutorial on Higher-Order Data Analytics for Temporal Network Data
All readings, video tutorials, and exercises are now freely available. Enjoy: http://www.thefunctionalart.com/2018/08/visualization-mooc-materials-available.html?m=1