Part 2: Let's play a few more games

Great work on the last project. This time, you will need to simulate multiple game shows hosted over several days. This means that your data will have a time dimension to it. More specifically, your data will have the shape (number of contestants, game shows, inputs size).

You will need to extend your model to incorporate this new feature. For this you will be using a TimeDistributed layer to allow the Dense layer to accept contestants from multiple game shows.

You have been provided with the weight initializer init, the prizes list from the previous exercise, a time-series input x and names which contains the names of the contestants. x is a (3,2,3) numpy array where names is a (2,3) Python list. In other words, you have 2 game shows (i.e. sequence length), each with 3 contestants (batch size) where each contestant has 3 attributes (input size).