Starting a weekly blog update with new things learnt in the week

Jun 16, 2019

James Clear, author of Atomic Habits, has a great collection of inspiring talks here: https://jamesclear.com/great-speeches
Kaggle Days 2019 SFO Playlist: https://www.youtube.com/playlist?list=PLqFaTIg4myu99Huiyr2ZojzN3dlYhe8rf
FastAI - Austria study group has a repo with starter material on fastai & pytorch here: https://github.com/MicPie/fastai-pytorch-course-vienna
Cheat sheets by the Amidi brothers at Stanford, on Deep Learning and other topics: https://stanford.edu/~shervine/teaching/
Nice set of articles on creating a RL gym environment for bitcoin trading:
- Part 1: https://towardsdatascience.com/creating-bitcoin-trading-bots-that-dont-lose-money-2e7165fb0b29
- Part 2: https://towardsdatascience.com/using-reinforcement-learning-to-trade-bitcoin-for-massive-profit-b69d0e8f583b
Optimus library that makes spark dataframes easy to use (similar to pandas): https://github.com/ironmussa/Optimus
See here for a cheat sheet: https://htmlpreview.github.io/?https://github.com/ironmussa/Optimus/blob/master/docs/cheatsheet/optimus_cheat_sheet.html
Tensorflow Meets playlist: https://www.youtube.com/playlist?list=PLQY2H8rRoyvyOeER8UNF-1zXaCKGLZVog
In particular, on tensorflow datasets: https://www.youtube.com/watch?v=QAlgqmttan0&list=PLQY2H8rRoyvyOeER8UNF-1zXaCKGLZVog&index=3&t=0s
Pipeline AI for deployment of ML models: https://github.com/PipelineAI/pipeline/tree/master/docs/quickstart/docker. Recording of workshop is here: https://www.youtube.com/watch?v=OhIa2cnGD8Y
Peter Norvig’s talk at Microsoft: https://www.microsoft.com/en-us/research/video/as-we-may-program/
Count Bayesie blog: https://www.countbayesie.com/blog/2016/5/1/a-guide-to-bayesian-statistics
Summer of AI tutorial on Pytorch: https://summerofai.com/lessons/
Clickbait analysis: https://www.linkedin.com/pulse/clickbaits-revisited-deep-learning-title-content-features-thakur/
Numerai submissions on EC2 Fargate