Why LSTM is better than RNN?
LSTMs are special Recurrent Neural Networks that learn from sequences like text or time-series data. They're exceptional at predicting what comes next in a sequence, making them perfect for tasks like language translation, text generation, and stock market forecasting.
What sets LSTMs apart is their ability to remember long-term dependencies. Traditional RNNs struggle to retain information from earlier in the sequence, a problem known as 'vanishing gradients.' LSTMs solve this with a unique structure comprising gates – the forget gate, input gate, and output gate. These gates regulate the flow of information, deciding what to retain and what to discard, making LSTMs capable of learning from long sequences without losing important context.