In this course, you will :
- Discover the fundamentals of Recurrent Neural Networks (RNN).
- Understanding how information flows through the network, and then seeing how to implement such models with Keras in the sentiment classification task
- Learn about the vanishing and exploding gradient problems that frequently occur in RNNs, as well as how to deal with them using GRU and LSTM cells.
- Learn how to prepare data for the multi-class classification task, as well as the distinctions between multi-class and binary classification (sentiment analysis).
- Learn how to use Keras to create models and evaluate their performance.
- Learn how to convert text data into the format required by the models.
- Recurrent Neural Networks and Keras
- RNN Architecture
- Multi-class classification
- Sequence to Sequence Models