Learning with Recurrent Neural Networks

Learning with Recurrent Neural Networks by Barbara Hammer provides an introduction to the principles, architectures, and applications of recurrent neural networks (RNNs). The book explains how RNNs process sequential data, their learning algorithms, stability issues, and practical use cases in areas like time-series prediction, speech, and pattern recognition. It serves as a concise resource for students and researchers interested in neural computation and sequence learning.