Скачать или смотреть BE544 Lecture 09 - Classification using Convolutional Neural Network (Contd.)

The video illustrates the concepts of overfitting and underfitting, along with various techniques to address these issues, such as regularization, dropout, data augmentation, batch normalization, and noise injection. It also clarifies the concept of data leakage, including its occurrence and methods to prevent it. Furthermore, it demonstrates the implementation of data augmentation, dropout, and efficient dataset preparation in Python code. Lastly, it covers accessing TensorBoard history, including displaying training and validation curves and applying smoothing techniques to enhance visualization.

All code used in the lectures will be available in my GitHub repository (https://github.com/HossamBalaha/BE-54...) in the "Lectures Scripts" folder.