Ask HN: How to get back into AI?
Analysis
The article is a request for resources to re-enter the field of AI, specifically focusing on areas that have emerged since the user's previous involvement. The user has a foundational understanding of neural networks and transformers, and is looking for materials to learn about diffusion models, large transformers (GPT*), Graph NNs, and Neural ODEs. The user prefers hands-on learning through Jupyter notebooks.
Key Takeaways
- •The user has prior experience in AI, specifically with neural networks and transformers.
- •The user is looking to learn about new advancements like diffusion models, GPT*, Graph NNs, and Neural ODEs.
- •The user prefers hands-on learning with Jupyter notebooks.
- •The user is seeking resources to facilitate a gradual re-entry into the field.
Reference
“I was involved in machine learning and AI a few years ago... Do you know of any good resources to slowly get back into the loop? ... I would especially love to see some Jupyter notebooks to fiddle with as I find I learn best when I get to play around with the code.”