smythfoam

Inbox

https://peterroelants.github.io/posts/gaussian-process-tutorial/

https://e2eml.school/transformers.html

https://philippschmitt.com/blueprints-for-intelligence/

https://courses.dibya.online/p/fastdeeprl

https://deep-learning-drizzle.github.io/

https://physicsbaseddeeplearning.org/intro.html

Simple Modifications to Improve Tabular Neural Networks https://arxiv.org/abs/2108.03214

https://d2l.ai/chapter_natural-language-processing-pretraining/bert-dataset.html

https://www.pythonlikeyoumeanit.com/index.html

https://mlstory.org/ PATTERNS, PREDICTIONS, AND ACTIONS

https://iclr-blog-track.github.io/blog/

https://www.mathphysicsbook.com/mathematics/

https://docs.google.com/presentation/d/1_tvzLKks83sYOKemfFeImCPnWtCQ-CHqmKK_3IQI1so/edit#slide=id.g1342fba2a33_0_0

https://udlbook.github.io/udlbook/

add a viz page

https://graphicsprinciples.github.io/

cv

https://szeliski.org/Book/

geometric/graph

https://arxiv.org/abs/2104.13478

https://arxiv.org/abs/1912.12693

https://geometricdeeplearning.com/lectures/

ps

https://amaarora.github.io/2021/03/13/optimizers.html

https://lilianweng.github.io/lil-log/2018/06/24/attention-attention.html

https://github.com/erebe/personal-server/blob/master/README.md

raschka: https://sebastianraschka.com/resources/ml-lectures-1

https://hackernoon.com/list-of-free-resources-to-learn-natural-language-processing-5bc4b76db552

https://arxiv.org/abs/2004.03705v1

http://neuralnetworksanddeeplearning.com/

https://news.ycombinator.com/item?id=23026750

https://twist.com/remote-work-guides/remote-team-communication?utm_source=doist_blog&utm_medium=referral&utm_campaign=blog_update

https://reeve.blog/blog/principles/

https://bookdown.org/ts_robinson1994/10_fundamental_theorems_for_econometrics/

add a deep page

https://huggingface.co/blog/simple-considerations

https://blog.slavv.com/37-reasons-why-your-neural-network-is-not-working-4020854bd607

https://github.com/d2l-ai/d2l-en

https://people.idsia.ch/~juergen/deep-learning-history.html

add deep structured page

Rossman: https://arxiv.org/abs/1604.06737

https://cloud.google.com/solutions/machine-learning/ml-on-structured-data-model-2

https://twimlai.com/twiml-talk-301-deep-learning-with-structured-data-w-mark-ryan/ https://www.manning.com/books/deep-learning-with-structured-data https://arxiv.org/abs/1604.06737 (paper of the ‘famous’ rossmann stores kaggle result). https://arxiv.org/pdf/1908.07442v1.pdf

rl

https://web.stanford.edu/class/psych209/Readings/SuttonBartoIPRLBook2ndEd.pdf?ref=mentorcruise

general se or not notebooks

https://www.kaggle.com/rtatman/six-steps-to-more-professional-data-science-code

grus hate

Foam

• Here you can write disorganised notes to be categorised later
• Bullet points are useful, but it could be free form text as well
• Sometimes it’s better to just get things off your mind quickly, rather than stop to think where it belongs
• But don’t let this list get too long
• Move information to more specific documents and link to them.
  • This helps you navigate between documents quickly
  • For example, you can Cmd+Click this: [todo]
• Some notes don’t end up making sense the next day
• That’s ok, you can just delete them!
  • You can always find them in your git history, if you really need it!