These are my existing ML notes which are a record of all the things I've learnt.
Here are the Papers that I'm currently reading/have read.
Elicit Machine Learning Guide: My current progress on the Elicit Machine Learning Reading List
[[LLM Fine Tuning Maven]] : A Maven Course on fine-tuning large language models
A Guide To Hyperparameters : These are some notes that I took about training hyper-parameters when fine-tuning models
Large Language Models : A quick introduction to what is a Large Language Model
Recommendation Systems : A quick dive into what a recommendation system is
Pytorch : A guide to using auto differentiation libraries in Machine Learning
[[Designing Machine Learning Systems]] : Some notes on Chip Huyen's Book
Machine Learning with PyTorch and Scikit-Learn : A guide on how to work with Pytorch for machine learning
[[RNN]] : A simplified implementation of RNNs in Pytorch
[[Retrieval Augmented Generation]] : How to do RAG
[[Chroma DB Chunking Guide]]