강의가 체계적이고 설명이 이해하기 쉽게 잘 되어 있어서 끝까지 완강했습니다. 덕분에 딥러닝 기초를 잘 다질 수 있었고, 현재는 오브젝트 디텍션 강의도 신청해서 열심히 듣고 있습니다. 좋은 강의 감사합니다!

King_God_0

딥러닝·CNN 핵심 이론부터 다양한 CNN 모델 구현 방법, 실전 문제를 통한 실무 딥러닝 개발 노하우까지,
Pytorch 기반의 딥러닝 CNN 기술 전문가로 거듭나고 싶다면 이 강의와 함께하세요 :)

권 철민

배움이 더 쉬워지는 9월의 할인

딥러닝 CNN 완벽 가이드 - Pytorch 버전

PyTorch

pytorch

Deep Learning(DL)

딥러닝

딥러닝실전프로젝트

컴퓨터비전

From core theories of deep learning and CNN to various CNN model implementation methods, and practical deep learning development know-how through real-world problems,
If you want to become a deep learning CNN technology expert based on Pytorch, join us in this lecture :)


dooleyz3525

입문

초급

중급이상

파이토치

Computer Vision(CV)

합성곱신경망

Deep Learning CNN Complete Guide - Pytorch Version

Course Introduction


An Overview of Deep Learning and Handling Tensors


Deep Learning Based Understanding - Gradient Descent


Deep Learning Based Understanding - Backpropagation and Activation Functions


Pytorch Framework - 01


Pytorch Framework - 02


Pytorch Framework - 03


Understanding CNNs


Weight Initialization, Batch Normalization, Drop Out, Learning Rate Scheduler, and Weight Decay


Dataset and DataLoader


Utilizing Pretrained Models and Fine-Tuning Training


Modularize ModelCheckpoint, EarlyStopping, and Trainer classes and use torchmetrics.


Image Data Augmentation


Advanced Image Data Augmentation - CutMix


Understanding CNN Models - AlexNet, VGG, GoogLeNet


Understanding CNN Models - ResNet Details and EfficientNet Overview


Comprehensive Practice 1 - Optimizing a Dog Breed Identification Model for 120 Breeds


Comprehensive Practice 2 - Kaggle Plant Pathology (Tree Leaf Disease Diagnosis) Competition


In conclusion,
