# Start here

Subject: Deep Learning

Exam: MT2

Reader: https://deep-learning-study-room.vercel.app/#mt2/read/9/mt2-c9-intro

Canonical: https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c9-intro/

This recurrent-network material is retained as an additional reference. The faculty update received on 12 October focuses MT2 on Units 3 and 4; use the TEE route for RNN study.

![At each time step, combine the new input with a summary carried from the previous step.](https://deep-learning-study-room.vercel.app/assets/figures/v_rnn_state.svg)

Diagram: At each time step, combine the new input with a summary carried from the previous step.. Labels: Combine the current input and the previous state | Combine the current input and the previous state | The new state depends on both paths. | Previous state | h at time t − 1 | Current input | x at time t | Combine | Weighted sum + | bias | Activate | New state h at t | The same recurrent weight matrices are used again at the next time step.

At each time step, combine the new input with a summary carried from the previous step. Tap the diagram to enlarge.