In the previous lessons, we saw that slightly complicating the movie dataset makes our simple perceptron model unsuitable for the classification task. We also theoretically saw that introducing a hidden layer with two neurons solves the problem. However, as an ML engineer, how do you know if this actually works for our movie dataset? We need to test our new MLP model with a hidden layer by implementing it in Python. Let’s try writing the Python code to create the neural network that classifies “Good” from “Bad” movies.

We’ll use the terms multi-layer perceptron and neural network interchangeably from this point onwards.

Similar to the perceptron model, we will follow the complete ML pipeline for our MLP also. Let's revisit it once again.

The ML process

For any complex problem that requires the computer to be able to identify patterns, there is an ML process to solve it.

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