2025 Learning Topics

Topics

Signal Processing

Since I've been playing with audio processing for fun and often am adjacent to Computer Vision applications at work I've been interested in signal processing.

In general the skill of analyzing data in the frequency domain seems to help one gain intuition for abstract similarities between audio, images or other types of data especially in the time domain.

Resources

• Mike X Cohen: applied courses for both signal processing, image processing and fourier transform
• Iain Explains: applied engineering examples of fourier transform

Linear Algebra

I want to improve my intuitions for Linear Algebra and advance into more applied topics. I remember the basics from my undergraduate studies but want to get to more advanced topics which prove to be useful for Signal Processing, Computer Vision, ML and Statistics.

Resources

• MIT 18.06 Linear Algebra Lectures
• Linear Algebra Done Right¹
• MIT 18.065: Matrix Methods in Data Analysis, Signal Processing, and Machine Learning

Statistics

A similar story as with Linear Algebra here. I think however with Statistics I could probably take a more theoretical approach as the courses from my undergrad were very applied and I believe my intuition for a topic is usually better when I take a more rigorous approach. Especially given this is second pass through the topic it usually makes sense to try formalizing the concepts.

Resources

• Statistical Inference Second Edition²
• Statistics for Mathematicians: A Rigorous First Course³

Computer Vision

I'm interested in doing a high-level overview of the concepts. I noticed that there are lecture notes from CS484: Introduction to Computer Vision which I will probably try to skim through for a high-level understanding. Understanding signal processing and the frequency domain is a huge aid for jumping into this topic.

Resources

• Computer Vision: Algorithms and Applications⁴
• Concise Computer Vision: An Introduction to Theory and Algorithms⁵

Minor Interest

Networks

I want to review the low-level protocol concepts to have a more solid understanding of the fundamentals. I took a course on this: CS456 Computer Networks which did go over things like TCP including the connection state machine.

Resources

• TCP/IP Illustrated, Volume 1: The Protocols⁶

LLMs

Continue to play with locally hosted LLMs. Possibly look into more customized models or how to improve my workflow with LLMs.

Books