It's interesting how perfectly you've captured the current frustration with scattered learning materials on finetuning; this structured, step-by-step roadmap sounds like a real lifesaver for anyone diving into LLM deployment. I especially appreciate the promise of balancing intuition with code, because honestly, after sifting through countless LoRA guides that either felt like a PhD thesis or just gave me a `pip install` command, a comprehensive aproach is a breath of fresh air.
Fantastic outline! Really looking forward to this course. As another comment pointed out, learning material on the LLM training lifecycle is really scattered and tends to be either a PhD thesis or a code repo without explanation. This course is gonna be different 🔥
@Miguel and Neural Maze - Starting to love the content and the sessions - I just finished phone calling agents and excited for Fine Tuning.
Do we have such detailed articles for RAG and Graph RAG ? I feel the articles are scattered , i am looking for unified way that explains multi-modal RAG - like images, tables, text in a much efficient way - various techniques .. I am sorry if that is covered - appreciate the link if you have
It's interesting how perfectly you've captured the current frustration with scattered learning materials on finetuning; this structured, step-by-step roadmap sounds like a real lifesaver for anyone diving into LLM deployment. I especially appreciate the promise of balancing intuition with code, because honestly, after sifting through countless LoRA guides that either felt like a PhD thesis or just gave me a `pip install` command, a comprehensive aproach is a breath of fresh air.
This is a real problem in the frontier AI space
Can't wait! all the essential topics will be covered here :)
glad you like it!!
This is gold!
Thanks!!
Excited!
let's goooo
looking forward to this pretty excited
amazing!!
Fantastic outline! Really looking forward to this course. As another comment pointed out, learning material on the LLM training lifecycle is really scattered and tends to be either a PhD thesis or a code repo without explanation. This course is gonna be different 🔥
@Miguel and Neural Maze - Starting to love the content and the sessions - I just finished phone calling agents and excited for Fine Tuning.
Do we have such detailed articles for RAG and Graph RAG ? I feel the articles are scattered , i am looking for unified way that explains multi-modal RAG - like images, tables, text in a much efficient way - various techniques .. I am sorry if that is covered - appreciate the link if you have
let's go! See you this Sunday, in the first office hours!