💯 “Despite its prevalence, censored time-to-event data is often overlooked, leading to dramatically biased predictions.” https://t.co/C8uvtPC6OM
— Erik Bernhardsson (@fulhack) March 2, 2019
💯 “Despite its prevalence, censored time-to-event data is often overlooked, leading to dramatically biased predictions.” https://t.co/C8uvtPC6OM
— Erik Bernhardsson (@fulhack) March 2, 2019
This is probably the best intro to probability (along with the associated lectures https://t.co/qUNs9NOxFP), now available online for free ❤ https://t.co/7J9dfgJDsH
— Radek Osmulski (@radekosmulski) March 2, 2019
This is a really great overview of many nice approaches to self-supervised learning for images https://t.co/aq9gbbIWYn
— Jeremy Howard (@jeremyphoward) February 28, 2019
Finally had a chance to watch @earowang's #RStudioConf talk on tidy time-series forecasting. Made me eager to dive into the tsibble and fable #rstats packages!
— Sharon Machlis (@sharon000) February 24, 2019
Video of the talk: https://t.co/eVc2k30kb5
tsibble: https://t.co/tmnPdLYL0o
fable: https://t.co/zG6ZA5jwzI
2 years, 250 pages, 1,219 commits, and 78,480 words:
— Christoph Molnar (@ChristophMolnar) February 21, 2019
I am very proud to say that today I published the 1st edition of "Interpretable Machine Learning". 🎉🎉🎉
Web: https://t.co/s4tyZz3f3B
Leanpub: https://t.co/OAIEB1YNzR pic.twitter.com/6ewrYcgDdb
Stumped on our 'Don't Overfit II' competition? 🤔It's a doozy! In this article,@Terrah27 explores hyperparameter optimization as a means of preventing overfitting — complete with examples. [READ] 👉 https://t.co/HHS9KWTM69 via @TDataScience
— Kaggle (@kaggle) February 20, 2019
So much to learn about #machinelearning & #artificialintelligence on #pydata videos, including:
— PyData (@PyData) February 20, 2019
"Data versioning in machine learning projects" by Dmitry Petrov — how to solve the issue of discrepancy between code & data files https://t.co/4B317wMMnq
Don't forget to subscribe!
Meanshift Clustering By Analogy https://t.co/eZ2bbpDzwV pic.twitter.com/a0FPS5Rc6a
— Chris Albon (@chrisalbon) February 18, 2019
Tensorflow-Cookbook - Simple Tensorflow Cookbook for easy-to-use https://t.co/HKgi7PNnBK
— Python Trending (@pythontrending) February 17, 2019
TensorFlow-Course - Simple and ready-to-use tutorials for TensorFlow https://t.co/3MyqzqssZA
— Python Trending (@pythontrending) February 17, 2019
So many things you can do with #Jupyter notebooks, including:
— PyData (@PyData) February 16, 2019
"Extending Jupyter with Google Cloud Storage file system backend" by Egor Bulychev—work with notebooks & other files directly in Google Cloud Storage:https://t.co/sWOOXsyLNI
Subscribe to #PyData on Youtube for more!
How powerful are Graph Neural Networks? Slides from my talk at ITA workshop in San Diego.https://t.co/K4syDPYe82 pic.twitter.com/n2KXooiKBC
— Jure Leskovec (@jure) February 15, 2019