Following along step-by-step in Excel like this makes it much easier to understand than just putting in code with Python.

Testing with Excel, which I use regularly, makes it much easier to understand.

A liberal arts student took this course to improve work efficiency. Although it was challenging at first since it was unfamiliar learning, the instructor taught it easily and provided examples, so I was able to learn without much difficulty. After implementing email automation, my work time has been tremendously reduced.

The step-by-step explanation method is good, but for greater efficiency, sharing flowchart-based explanations and executable attachments would be helpful.

This is the kind of class that makes you look forward to the next session. It's like watching Netflix. I've always been interested in deep learning, but I couldn't start because I didn't know Python. Finding 먼진's lecture was a stroke of luck. If I had been good at Python, I would have only been left with questions like, "Why? What is this even doing?" due to the invisible calculation process, and my interest would have quickly waned. But you showed us what processes are happening in Excel, which made me want to keep watching the next lecture. I will fill in the detailed content myself. Thank you for the great lecture!

Most introductory deep learning courses focus on using functions and looking at the resulting data, so I was curious about the process of creating and training models. This lecture was exactly what I wanted. It was fun to visually see the Excel implementation with easy examples. Thank you!

Understanding machine learning concepts was easy with the explanation using Excel.

I am currently studying the generation model. I have listened to the lecture before, but I didn't leave a review. Personally, I found it interesting because the instructor only taught me the things I needed to know.

It was a bit difficult for me as a liberal arts major in terms of mathematics, but I think it's the best for understanding deep learning concepts! Thank you!

thank you