What are the best techniques for using gated recurrent units in machine learning algorithms?
Gated recurrent units (GRUs) are a type of recurrent neural network (RNN) that can handle sequential data, such as natural language, speech, or video. GRUs can learn long-term dependencies and capture complex patterns in the data. However, they also have some challenges, such as choosing the right architecture, hyperparameters, and regularization techniques. In this article, you will learn some of the best practices for using GRUs in machine learning algorithms.