The course is crafted to reflect the in-demand skills in the marketplace that will help you in mastering the key concepts and methodologies of RL and deep RL, along with several practical implementations. This course will help you know the theory and practical aspects of reinforcement and deep reinforcement learning.
In this self-paced course, you will learn how to use TensorFlow 2 to build recurrent neural networks (RNNs). You will learn about sequence data, forecasting, Elman Unit, GRU, and LSTM. You will also learn how to work with image classification and how to get stock return predictions using LSTMs. We will also cover Natural Language Processing (NLP) and learn about text preprocessing and classification.