Next, the demo creates a 65-32-8-32-65 neural autoencoder. An autoencoder learns to predict its input. Therefore, the autoencoder input and output both have 65 values ... programming language, ...

then use the output of the lower-layer autoencoder as the input for the next layer, continuing training and progressively extracting deeper features. In this way, the model is able to gradually ...

Finally, the output of the second autoencoder is used as a recommendation prediction for the model. Future work can focus on trying to introduce other deep learning models to mine additional ...