Artificial Intelligence

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