Link to the course is here . Every day there are lectures from renowned research in the field of LLM, Neuroscience, and philosophy covering the foundations of LLM. This post updates the summarizes of the talks with my personal commentaries, from June 3rd to June 14th. I prioritize talks from practitioners in AI. Lecture One: Dimensionality and Feature Learning in Deep Learning and LLMs
Notice that for this course (and all UCLA courses) the slides are intellectual properties of the instructor; therefore the post is just my own curated notes and projects based on the course (which are therefore my own intellectual properties). The notes here should consist of two parts: My learning journey, taking this challenging course as someone who has no fluid mechanics background (although plenty of backgrounds in applied mathematics and machine learning)....
Week 1 This week, we introduced Fluid Mechanics from a “third grade perspective”. Professor Roper introduced to us fluid mechanics in a lively manner; in the first lecture (referred to as “3rd grade definition”, intended for kids in 3rd grade), he defined fluid as that which takes shape of its container. This definition sounds like one of the natural philosophers from ancient Greece. This class is about “what makes fluid flow” and “what stops them from flowing”, and we listed the following:...