This course covers the implementation of advanced RNN models that overcome the drawbacks of plain RNNs. We will particularly look at LSTM, GRU-based model, Bi-directional and Stacked RNNs. This course is part of The Deep learning with TensorFlow learning path– complete this path to build and deploy Deep learning models using TensorFlow.
Requirements
- Prior knowledge and experience in Machine Learning and Python is assumed. Completion of the following courses is a mandate: Building Blocks of Deep Learning, Neural Networks, Image Recognition with Convolutional Neural Networks (CNN), Deep Learning for Text: Embeddings, Deep Learning for Sequences.
