Top 20 RNN, LSTM Interview Questions and Answers (Part 2 of 2)
Last Updated on January 26, 2026 by Editorial Team
Author(s): Shahidullah Kawsar
Originally published on Towards AI.
Machine Learning Interview Preparation Part 13
RNN (Recurrent Neural Network) is used for sequence data like text or daily sales. It processes one step at a time and keeps a hidden state that stores past information. This helps it learn patterns over time. LSTM (Long Short-Term Memory) is an improved RNN. Basic RNNs often forget older information when sequences are long. LSTM fixes this using gates that control what to remember and what to forget. Because of this, LSTMs handle long-term dependencies better and train more reliably than vanilla RNNs.
The article discusses RNNs and LSTMs in the context of machine learning interview preparation, posing various questions and answers that test one’s understanding of these models. It covers fundamental concepts, operational mechanisms, and common challenges faced when using RNNs versus LSTMs, including long-term dependencies, gradient issues, and architectural differences. The content is structured as a quiz, with multiple-choice questions to engage the reader and reinforce learning about RNNs and LSTMs.
Read the full blog for free on Medium.
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