Hi everyone,
I am a beginner in fine-tuning large language models (LLMs) like T5 or BERT and would love some guidance on the learning path. Currently, I am learning Python, Pandas, and NumPy. I want to understand what specific topics I should focus on next to fine-tune these models effectively.
From my research, I understand that I need to learn Machine Learning (ML), Natural Language Processing (NLP), and Deep Learning (DL), but I am looking for specific subtopics within each category that are most relevant for fine-tuning LLMs.
Could you please suggest a structured learning roadmap with subtopics?