Shin Kyung-sik's Deep Learning - Gradients and PyTorch's Autograd

Hello everyone, students!

Starting today, we're launching our full-scale deep learning course curriculum, so we're here to guide you😃

The [Shin's Deep Learning (ShinDL)] curriculum that I personally create covers deep learning systematically from the basics to actual paper-level lectures,

This is a curriculum with the goal of perfectly understanding deep learning technology by directly implementing all the techniques yourself!

Additionally, since the field of deep learning is so broad, the course is structured as modularized lectures covering specific topics rather than large-volume lectures.

This newly opened course is the first lecture in the [Shin Kyung-sik's Deep Learning] curriculum, designed to properly understand deep learning

A course that teaches 'differentiation', an essential mathematical foundation, and PyTorch framework's autograd technology

[Gradients and PyTorch's Autograd]입니다.

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

Going forward, we plan to cover not only basic deep learning techniques but also conduct practical projects based on deep learning papers.

If you are preparing to study deep learning, please follow the curriculum step by step starting from this lecture😃

Additionally, please note that the second deep learning lecture [Gradient Descent] is scheduled to open next week!

I will do my best to provide even better lectures in the future!

Thank you.

Best regards, Shin Kyung-sik