Exercise

# Part 1: Enter to win amazing prizes

In this exercise, you will learn about the `Dense`

layer. Why not do that with a fun exercise? Imagine there's a game show where prizes are determined by a neural network. The contestant enters

- the number of siblings,
- the number of coffees had today and
- if they like tomatoes or not,

and the model predicts what the contestant will win.

To implement this, you will be using Keras. You will need to create a model with an input layer which accepts three features (the number of siblings as an integer, the number of coffees as an integer and if they like tomatoes or not as a 0 or 1). Then the input goes through a Dense layer which outputs 3 probabilities (i.e. probabilities of winning a car, a gift voucher or nothing).

`Input`

and `Dense`

layers as well as a `Model`

object from Keras are already imported. You are also provided a weight initializer called `init`

to initialize the Dense layer.

Instructions

**100 XP**

- Define an input layer which
**only**accepts 3 contestants (batch size), where each contestant has 3 inputs: sibling count, number of coffees and tomato preference (input size). - Define a
`Dense`

layer which has 3 outputs,`softmax`

activation and`init`

as the initializer. - Compute the model predictions for
`x`

using the defined model. - Get the most probable prize (as an integer) for each contestant.