This page is intended to showcase some of incredible academic as well as some non-academic resources that I have personally benefited from. maybe it can come of use to you too!
Applying to Grad School 🚸
Ranking Lists: US News, QS Rankings, Times Higher Education
Statement of Purpose writing guide: Graduate Admissions Essays, Machine Learning SOP templates
General Guide: Tim Dettmers' Ph.D. Application walkthrough
Surviving Grad School 🧗
How to's of academic literature reading: Jason Eisner, Andrew Ng
How to's of academic paper writing: Jennifer Widom's GuideJ. Foerster's Guide
How to's of peer reviewing: Mila paper-swap guide, EMNLP guidelines, Wiley's must-watch 10 tips, Wiley's List
Mental Health: Autumn Turpin's Blog, Chuck Fidler's Blogpost, APA Guide 

Networking (a must!): Northeastern University's tipsCheeky Scientist, Grad Student Way
ML Mentorship: mementor.net, NLR's Spreadsheet
Con-grads!🎊🎓
Job Interview Guide: A nerd's guide, HHMI Guide, Mila Guide, Mila Guide (unofficial), Google Interview Warmup, Nato Lambert's Blog
AI Residency Lists: Google AIFAIR, Microsoft, IBM, Intel, Nvidia, Uber

AI Residency Cover Letter Guide: Colin Raffel's BlogOleksii Sidorov's template
AI Residency Experience: Joe Antognini's Blog

Postdoc Application Guide: Harvard NeuroDEI
Interview Prep:
Intro to ML Interviews Book, Cracking the Coding Interview, Data Science Prep SheetSteve Nouri's Guide
Academic Cover-Letters & Résumé Guide: Harvard
Assorted🍦
Reinforcement learning (Videos): David Silver, Sergey Levine

Special Topics in ML: Sharon Y. Li, Intro Notes on Causal Inference, Mila Neural Scaling Law Group
Foundations of Deep Learning: Soheil M. Feizi (YouTube, Jupyter Notebooks), Dive into DL

ML Systems Design: Chip Huyen [1]Chip Huyen [2]
MLOps: Azure, Google Cloud
ML Research groups: Harvard ML Foundations
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