I write code sometimes


Machine Learning Roadmap

I'm planning to break into the ML side of things - here's what I have in mind.


Looking to break into ML and I kind of lose track of what I've been doing so I figured I'd just document everything here.

The Progress


  • Finished tidying up a repo with notes that I'd taken down on Karpathy's course. Currently we have part 1,2 and 3 in there.
  • Read up a bit on the paper that he mentioned - A Neural Probablistic Model which mentions the use of a real-number vector to represent words. This is currently used extensively in NLP and is known as word embeddings but back then I'm sure it must have been a novel idea.
  • Played around with the new Next Auth Kysely integration and Resend and wrote a quick article here - Started working on a small tool as part of Buildspace s4 to help people prep for interviews using GPT-4 and some other models called Prep With AI which uses a bunch of the different things that I wrote about


I wasn't able to do as much as I wanted due to reservice commitments but I did manage to get a few things done.

  • Discovered Andrej Karpathy's Zero to Hero course and plan to start working through it through August. So far I've finished up with his intro to neural networks and I built a basic binary classifier which has ~42% accuracy using a custom neural network I coded in vanila python. Finished up with the first 2 chapters of his course and I'm really enjoying it so far.

  • Finally figured out how to deploy langchain on AWS lambda and spent my entire weekend trying to automate a 20 min task with aws sdk


June has just started and my plan now is to work on more applications of LLMs. I believe that using LLMs to augment my learning will help tremendously when it comes to generating new insights and finding interesting angles to explore.

The plan is to build a local LLM using gpt to be able to query and discover new insights about my previous notes and chats. I tried implementing a basic clone with memory and embeddings here but ended up getting side tracked with other ideas.

I also started experimenting with Open AI Functions and built out a simple classifier using Yake and GPT that was able to classify places that I had been to before using my reviews and other metadata ( Link )


I've managed to finish up Part 1 of Fast AI's course and boy have I learnt a lot about machine learning in general. The course seems to cover a lot more of traditional machine learning techniques and there's a lot which I'll definitely need to revisit. You can read my notes here FastAI Part 1