In this episode, we discuss the bane of many machine learning algorithms – overfitting. It is also explained why it is an undesirable way to learn and how to combat it via dropout.
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The paper “Dropout: A Simple Way to Prevent Neural Networks from
Overtting” is available here:
Andrej Karpathy’s autoencoder is available here:
Recommended for you:
Overfitting and Regularization For Deep Learning –
Decision Trees and Boosting, XGBoost –
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