AI, NLP, Deep Learning, Lstm, TensorFlow.
the exploitation of modern parallel processing technologies, leading to longer training times. Despite these challenges, RNNs remain a foundational architecture for sequence data analysis. Use Cases RNNs find applications in Natural Language Processing (language modeling, machine translation),