Course Content
Part – 8
Recurrent Neural Network (RNN), Long Short Term Memory (LSTM) And Gated Recurrent Unit (GRU)
- Understand about textual data
- Pre-processing data using words and characters
- Perform word embeddings by incorporating the embedding layer
- How to use pre-trained word embeddings
- Introduction to RNNs – Recurrent layers
- Understanding LSTM and GRU networks and associated layers
- Hands-on use case using RNN, LSTM, and GRU
- Recurrent dropout, Stacking recurrent layers, Bidirectional recurrent layers
- Solving forecasting problem using RNN
- Processing sequential data using ConvNets rather than RNN (1D CNN)
- Building models by combining CNN and RNN