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.