Long Short Term Memory vs Simple RNN

Developers should learn LSTM when working on projects that require modeling dependencies in sequential data, such as time-series forecasting (e meets developers should learn simple rnns when working on tasks involving sequential data, such as natural language processing (e. Here's our take.

Long Short Term Memory

Nice Pick

Developers should learn LSTM when working on projects that require modeling dependencies in sequential data, such as time-series forecasting (e

Pros

• g
• Related to: recurrent-neural-networks, gated-recurrent-units

Cons

• Specific tradeoffs depend on your use case

Simple RNN

Developers should learn Simple RNNs when working on tasks involving sequential data, such as natural language processing (e

Pros

• g
• Related to: long-short-term-memory, gated-recurrent-unit

Cons

• Specific tradeoffs depend on your use case

The Verdict

Use Long Short Term Memory if: You want g and can live with specific tradeoffs depend on your use case.

Use Simple RNN if: You prioritize g over what Long Short Term Memory offers.

The Bottom Line

Long Short Term Memory wins

Developers should learn LSTM when working on projects that require modeling dependencies in sequential data, such as time-series forecasting (e