Exercise

# Specifying a model

You will build a simple regression model to predict the orbit of the meteor!

Your training data consist of measurements taken at time steps from **-10 minutes before the impact region to +10 minutes after**. Each time step can be viewed as an X coordinate in our graph, which has an associated position Y for the meteor orbit at that time step.

*Note that you can view this problem as approximating a quadratic function via the use of neural networks.*

This data is stored in two numpy arrays: one called `time_steps`

, what we call *features*, and another called `y_positions`

, with the *labels*.
Go on and build your model! It should be able to predict the y positions for the meteor orbit at future time steps.

Keras `Sequential`

model and `Dense`

layers are available for you to use.

Instructions

**100 XP**

- Instantiate a
`Sequential`

model. - Add a Dense layer of 50 neurons with an input shape of 1 neuron.
- Add two Dense layers of 50 neurons each and
`'relu'`

activation. - End your model with a Dense layer with a single neuron and no activation.