My name is Jonathan! I’m a 4th year Data Science Honors student at UC Berkeley interested in Software Engineering, Data Science and Machine Learning. I’ve done both internships in industry and research with faculty in my time as an undergraduate but my background is primarily in AI research. I’ve worked on deep learning, LLM finetuning and graph neural net research at Lawrence Berkeley National Lab (LBNL) and Berkeley Artificial Intelligence Research (BAIR).
Throughout college I learned that the best way for me to retain information long term is to write it down. If I wanted to learn short term, mnemonics, route dictation (which I guess is technically writing) and verbal rephrasing is enough. However, when it comes to retaining information long term I’m a very writing-based learner. For example to learn concepts I read/hear/see it in class then –> write it down in my own words. To build skills and proficiency in problem solving I expose myself to some basic scaffolding problems –> write down a deconstruction of the scaffolding problem in detail (question wording cues, relevant concepts, approaches, etc) –> build up a library of previous questions I’ve seen to apply to new problems.
As I approached taking upper division technical classes and prepping for technical interviews I found that I couldn’t scale to the level of technical depth I needed. I needed stronger retention of concepts and skills so I started taking down a lot of written notes, usually onto google docs. However, my notes docs (even when I tried to optimize) would regularly go past a hundred, two hundred even three hundred pages. It was just way too laggy and didn’t scale well. So I started this website.
It’s honestly meant to be a resource for myself first and foremost, sorting a library of all the major technical concepts and problems I’ve ever been exposed to. However, if it also helps you that’s great!