In this Deep Learning explained series video, we discuss Regularization, a common method used to combat overfitting in Automatic Speech Recognition (ASR). We explore techniques such as L1, L2, and Dropout regularization, delving into the underlying logic behind these methods. Additionally, we establish the connection between Regularization and neural networks, providing a comprehensive understanding of this technique's role in improving model performance.