[Application] Creating a PyTorch Deep Learning Model: Utilizing Artificial Neural Networks

This is a practical course where you will learn how to actually build computer vision and deep learning models using PyTorch. Many learners understand deep learning theory but struggle with the actual process of implementing and training models. In this course, we start with the basic concepts of image processing and move on to understanding and directly implementing key deep learning models such as CNN, LeNet, AlexNet, VGGNet, Inception, and ResNet. Furthermore, you will learn the latest computer vision technologies, including Object Detection, Semantic Segmentation, Instance Segmentation, and GAN, through hands-on practice. Through this course, learners will acquire the practical skills to build and train real-world deep learning models using PyTorch.