This project compares the performance of LSTM (Long Short-Term Memory) neural networks implemented in Python and Rust for sequence-to-sequence translation tasks. A Python implementation using PyTorch ...

Why LSTM? LSTM is designed for sequential data. Text has order — the meaning of a word depends on what came before it. Regular RNNs forget early words due to vanishing gradients. LSTM solves this with ...

This demo from Dr. James McCaffrey of Microsoft Research of creating a prediction system for IMDB data using an LSTM network can be a guide to create a classification system for most types of text ...