[QUESTION] Chapter 10 Exercise 10 Factor parameter

Good day, I'm having a bit of trouble understanding why the value of **1.005** was chosen for the **` factor`** parameter. I know it's supposed to be an increment by 0.5% at each iteration and that the new learning rate will be` new_lr = old_lr * factor`, but I don't get where that value (1.005) came from.

This is the code:
```
model.compile(loss="sparse_categorical_crossentropy",
optimizer=keras.optimizers.SGD(learning_rate=1e-3),
metrics=["accuracy"])
expon_lr = ExponentialLearningRate(factor=1.005)
```

- **Notebook**: 10_neural_nets_with_keras
- **Cell**: 119