Dropout Regularization | Deep Learning Tutorial 20 (Tensorflow2.0, Keras & Python)

Overfitting and underfitting are common phenomena in the field of machine learning and the techniques used to tackle overfitting problem is called regularization. In deep learning, dropout regularization is used to randomly drop neurons from hidden layers and this helps with generalization. In this video, we will see a theory behind dropout regularization. We will then implement artificial neural network for binary classification problem and see how using dropout layer can increase the performance of the model.

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Code: https://github.com/codebasics/deep-learning-keras-tf-tutorial/blob/master/13_dropout_layer/dropout_regularization_ann.ipynb
CSV file: https://github.com/codebasics/deep-learning-keras-tf-tutorial/blob/master/13_dropout_layer

Next video: https://www.youtube.com/watch?v=JnlM4yLFNuo&list=PLeo1K3hjS3uu7CxAacxVndI4bE_o3BDtO&index=21

Previous video: https://www.youtube.com/watch?v=2osIZ-dSPGE&list=PLeo1K3hjS3uu7CxAacxVndI4bE_o3BDtO&index=19

Deep learning playlist: https://www.youtube.com/playlist?list=PLeo1K3hjS3uu7CxAacxVndI4bE_o3BDtO

Machine learning playlist : https://www.youtube.com/playlist?list=PLeo1K3hjS3uvCeTYTeyfe0-rN5r8zn9rw

Prerequisites for this series:   
1: Python tutorials (first 16 videos): https://www.youtube.com/playlist?list=PLeo1K3hjS3uv5U-Lmlnucd7gqF-3ehIh0    
2: Pandas tutorials(first 8 videos): https://www.youtube.com/playlist?list=PLeo1K3hjS3uuASpe-1LjfG5f14Bnozjwy
3: Machine learning playlist (first 16 videos): https://www.youtube.com/playlist?list=PLeo1K3hjS3uvCeTYTeyfe0-rN5r8zn9rw  


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DISCLAIMER: All opinions expressed in this video are of my own and not that of my employers'.