This Obsidian vault contains notes on just about everything I've learned about AI, or at least the stuff that I thought were important enough to write down. In other words, Hypomnemata.
Obsidian has some nice features like forward and backward links, graph views, etc., but all the notes are just markdown, so you can use them in any markdown editor or viewer.
To use this vault in Obsidian:
- Clone this repo locally.
- In Obsidian, click File > Open Vault.
- Click the button next to Open folder as vault.
- Select the local repo.
I've tried to organise the notes into folders by topic, but it's not perfect. [[AI/Machine Learning & Data Science/README|Machine Learning & Data Science]] contains the bulk of the notes, from basic concepts to more advanced. [[AI/Research Paper Explanations/README|Research Paper Explanations]] contains notes which I usually take while reading research papers. I try and make these as informative as possible, with images, diagrams, etc. The research papers are usually seminal papers in their respective fields.
Arthur Samuel (1959)
Machine Learning: Field of study that gives computers the ability to learn without being explicitly programmed.
Tom Mitchell (1998)
Well-posed Learning Problem: A computer program is said to learn from experience E with respect to some task T and some performance measure P, if its performance on T, as measured by P, improves with experience E.
![[Pasted image 20250928095605.png|center]]