I'm still in the early stages of the course, but the visual materials are excellent. It's just my personal opinion, but I find it easier to understand than the classic book "CODE."

Thank you for the great lecture.

I like it

This is a lecture that clearly explains why you need to learn linear algebra for AI. Rather than just focusing on formulas, it helps you understand the underlying meaning within them. Although the lecture duration itself isn't long, it may take some time to complete as you savor the deeper implications, but that time will be highly meaningful. (I am also focusing on understanding rather than just finishing; if I find something difficult, I go back to the beginning and rewatch it.) =======This is a reply to the instructor's post.============== It's not that the lecture is difficult, but rather that I feel I shouldn't just let the content pass by if I want to truly grasp the essence and the relationship between linear algebra and AI. So, I keep reflecting and listening repeatedly. I really love lectures like this one that foster intuition and focus on the essence rather than just formulas (such as comparing the relationship between geometry and algebra in linear algebra). The current lectures are already excellent, but I'm even more excited to hear that you plan to improve them further. Thank you! ^^