It was a great help in reviewing the theory because you went into detail about concepts like loss function and optimizer that I didn't know much about and used. I'm looking forward to the intermediate course lecture!!

sguys996119

This course teaches the “core concepts” of deep learning required to work in the deep learning field and the practical skills required to perform actual deep learning projects through hands-on training using PyTorch.

peterbyun969574

Complete mastery of deep learning theory + PyTorch practice

Thank you for taking the class :) And I'm glad it was helpful! I'll prepare harder for the next class and open it!

이론과 실습 한 번에

이론 실습 모두

개념정리

딥러닝기초

딥러닝모델

자연어처리

딥러닝 현업에 종사하기 위해 필요한 딥러닝의 “핵심 개념”을 배우고 PyTorch을 활용한 실습을 통해서 실제 딥러닝 프로젝트를 수행하는데 필요한 실무를 가르쳐주는 강의입니다.

변정현

입문

초급

중급이상

Deep Learning(DL)

딥러닝

파이토치

PyTorch

Computer Vision(CV)

컴퓨터 비전

자연어처리(Natural Language Processing)

transformer

딥러닝 이론 + PyTorch 실무 완전 정복

강의 소개

PyTorch 환경 설정 및 PyTorch의 기초

딥러닝이란?

손실 함수 (Loss Function)

Advanced Topics in Loss Function (손실 함수 심화)

경사 하강법 (Gradient Descent)

Advanced Topics in Gradient Descent (경사 하강 심화)

활성 함수 (Activation Function)

최적화 (Optimization)

PyTorch로 만들어보는 Fully Connected NN!

정규화 (Regularization)

학습 속도 스케쥴러 (Learning Rate Scheduler)

초기화 (Initialization)

표준화 (Normalization)

Convolutional Neural Network (CNN)

Recurrent Neural Network (RNN)

Attention과 Transformer