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  3. Introduction to Deep Learning with Keras

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.