I finished it today ^^ 

It was a great lecture that helped me a lot. 
In addition to CNN, it was also an experience where I could learn basic knowledge related to deep learning. 

I'm looking forward to the Advance lecture. 

If you build basic knowledge with this lecture at first, you can save a lot of time by finding and interpreting materials yourself, so I recommend it to others.

bhkim

From core theories of Deep Learning and CNN to implementation methods of various CNN models, and practical Deep Learning development know-how through real-world problems,
If you want to become a Deep Learning CNN technology expert, join us in this lecture :)


dooleyz3525

인프런 10주년! 사랑주간 전체 할인

A Complete Guide to Deep Learning CNN - TensorFlow Keras Version

입문

초급

중급이상

Deep Learning(DL)

합성곱신경망

텐서플로

Tensorflow

케라스

Keras

캐글(Kaggle)

Kaggle

Course Introduction and Setup

Deep Learning Basics - Overview and Gradient Descent

Understanding Deep Learning - Error Backpropagation, Activation Function, Loss Function, Optimizer

Keras Framework

Understanding CNN

Implementing CNN Models and Applying Basic Performance Improvement Techniques

Understanding Data Augmentation - Using Keras ImageDataGenerator

Using Pre-trained CNN Models and Understanding the Keras Generator Mechanism

Augmentation using Albumentation and Keras Sequence

Dissecting Advanced CNN Models - AlexNet, VGGNet, GoogLeNet

Breaking Down Advanced CNN Models - ResNet Details and EfficientNet Overview

Fine-tuning of Pre-trained Models and Application of Various Learning Rate Schedulers

Comprehensive Practice 1 - 120 Dog Breed ID Model Optimization

Comprehensive Practice 2 - Kaggle Plant Pathology (Plant leaf disease diagnosis) Competition