Shin Kyung-sik's Deep Learning - Gradient-based Linear Regression (2)

Hello, I'm Engineering Hyung😃

Starting today, I plan to upload deep learning-based computer vision lectures at a fast pace!

The first course, [Image Basics for Computer Vision], which covers the essential image fundamentals you must master before learning computer vision, has been released.

And a free course [Introduction to Computer Vision], which provides a brief introduction to computer vision, has also been released.

Image Basics for Computer Vision: https://inf.run/8x7Xn

Introduction to Computer Vision: https://inf.run/EzBfS

More than 10 computer vision lectures are scheduled to be uploaded during this May, so please stay tuned😃

PS) Since I am currently in a situation where I need to create the computer vision lectures immediately, I will produce the basic deep learning lectures in parallel with the computer vision lectures starting from mid-June.

Hello students 😃

From basics to professional level, systematically covering deep learning - [Shin Kyungsik's Deep Learning] fourth lecture [Gradient-based Linear Regression (2)] is now open!

(Course Link: https://inf.run/ymv1P)

This is a lecture where you learn how to implement the code directly implemented in Gradient-based Linear Regression (1) into practical code using PyTorch's features. It is also a lecture where you theoretically learn about the necessity of data preprocessing, theory, and its impact on learning, and implement it with practical code.

Those following my All About AI curriculum would benefit from taking advantage of the open discount period😃

Additionally, the follow-up lecture [Gradient-based Linear Regression (3)] is scheduled to open sometime next week.

I will always do my best so that we can work together diligently to create a deep learning world!

Thank you.

Best regards, Shin Kyung-sik