recommends
Sometimes I come across worthwhile machine learning stuff, open source tools, fascinating research papers and eloquent blogs which I feel are really helpful. Or maybe just an inspiring story/podcast. I often find myself in situations trying hard to recollect a past find. 🤔
“What was that resource?? Damn! I don’t remember.”
To avoid such circumstances, recently, I started this page. This not only solves problem of idea documentation, but also helps me quickly point people to this place for something I recommend. It is also worth peregrinating to the past and looking at these resources.
tl’dr: Things I like and think other people will appreciate.
Books
- Dive Into Deep Learning [ d2l.ai ]
- Python Machine Learning by Sebastian Raschka [ link ]
- ISLR: An Introduction to Statistical Learning [ link ] [note: super excited about version 2021]
- Deep Learning by Goodfellow [ link ]
- Michael Nielsen’s mini book on Neural Networks [ link ]
Blogs
- colah’s blog [ link ]
- ezyang’s blog [ link, podcast ]
- Chip Huyen’s blog [ link ]
- Distill.pub [ link ]
- Jay Alammar’s Blog [ link, youtube ] [note: Attention & Transformer blogs ❤️]
- Machine Learning Bites [ link ]
- How to read more books [ link ]
- Roadmap to Data Science [ link ] [note: slightly outdated but still good for someone who wants to begin (A lot of people want to know how to get started in ML; this is my answer).]
- The cost of an open source contribution by Ralf Gommers [ link ]
- Thoughts on recruiting [ link ]
- explained.ai [ link ]
- Matthew Rocklin’s Blog [ link ] [note: OSS Python’s Data Science Ecosystem]
- Mike McQuaid’s Blog [ link ] [note: nice OSS development thoughts]
- Thomas Viehmann’s Blog [ link ] [note: interesting PyTorch stuff]
- Quansight Labs Blog [ link ]
OSS Tools
- Docsify [ github , demo ]
- Just the Docs [ github , demo ]
- google-research/disentanglement_lib [ github ] [note: nice readme to steal ideas from]
- alvinwan/neural-backed-decision-trees [ github ] [note: nice readme to steal ideas from]
- carbon [ link ]
- hackmd [ link ]
- Executable Books [ link, example ]
- thomasjpfan/slides-template-hugo [ github ] [note: neat way to create slides using markdown]
Misc
- 3Blue1Brown [ youtube ] [note: Essence of Linear Algebra, Calculus & Neural Networks ❤️]
- vlgiitr/DL_Topics [ github ]
- You Need To Know CSS [ link ]
- Kunal Shah talks about building Cred [ youtube ]
- http://jessachandler.com/ [ link ] [note: interesting portfolio template]
- Go by Example [ link ]
- CppCast [ podcast ] [note: podcast for C++ developers by C++ developers]
- Travis Oliphant on Lex Fridman Podcast: NumPy, SciPy, Anaconda, Python etc. [ youtube ]
- Prompt injection: what’s the worst that can happen? [ link ]
- Securing LLM Systems Against Prompt Injection [ link ]
- Jailbreaking LLMs: Techniques, Examples, Prevention Methods [ link ]
- Are you a cookie thief? [ link ]
- Projecy Iceman: Anders Hofman [ link , youtube ]
- Training vs. Exercise | Rich Roll Podcast [ youtube ]
- Podcast: Yashish Dahiya | PolicyBazaar Founder/CEO [ youtube ]