Long Short-Term Memory Networks (LSTMs) focuses on a powerful type of recurrent neural network designed to learn long-term dependencies in sequential data. It enables models to remember important information over long sequences while forgetting irrelevant details using specialized gating mechanisms. This training explains how LSTMs work using input, output, and forget gates to control information flow through time steps. It also covers applications in natural language processing, speech recognition, time-series forecasting, and sequence prediction tasks. You will learn how organizations use LSTMs to handle complex sequential patterns in real-world AI systems. The course also highlights best practices for tuning, optimizing, and deploying LSTM-based deep learning models.
Showing the single result
