It was a time where I could deeply understand CNN while looking at the code. I'll continue right into the follow-up lectures. Thank you!

seunghun32461674

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

Deep Learning CNN Complete Guide - Pytorch Version

PyTorch

pytorch

Deep Learning(DL)

딥러닝

딥러닝실전프로젝트

컴퓨터비전

입문

초급

중급이상

파이토치

Computer Vision(CV)

합성곱신경망

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,
