# What you should understand before optimization

Subject: Deep Learning

Exam: MT2

Reader: https://deep-learning-study-room.vercel.app/#mt2/read/4/mt2-c4-s15

Canonical: https://deep-learning-study-room.vercel.app/read/dl/mt2/section/mt2-c4-s15/

You should be able to explain why a target and prediction differ, compute a weighted sum, choose an activation, measure a loss, find a one-neuron gradient and update a weight. If these steps are weak, repeat the first training example and the ReLU backprop example. They contain the entire calculation pattern that the next chapters extend.

![These four operations form the training loop used by the optimizers in the next chapter.](https://deep-learning-study-room.vercel.app/assets/figures/v_training_loop.svg)

Diagram: These four operations form the training loop used by the optimizers in the next chapter.. Labels: The four operations in one training step | The four operations in one training step | Repeat this sequence using the current parameters. | Predict | Forward pass | Measure error | Compute loss | Find | gradients | Backpropagation | Adjust | Optimizer | update | Calculate all gradients before replacing the old weights.

These four operations form the training loop used by the optimizers in the next chapter. Tap the diagram to enlarge.