Building and compiling the model

Now, let's build a simple neural network.

In this section, we will add the layers we'll use in our deep learning model. Let's get started:

1. First, we will import tensorflow, keras, and layers: 

In[26]: import tensorflow as tf
In[27]: from tensorflow import keras
In[28]: from tensorflow.keras import layers

2. Now, we can build our model. First, we are going to use Sequential() with two hidden layers and output a single continuous value. We have a wrapper function called model_building for this. When we compile the model, we need to choose a loss function, an optimizer, and accuracy metrics. We used RMSprop as the optimizer, mean_square_error as the loss function, and mean_absolute_error and mean_square_error as the required metrics. Mean Squared Error (MSE) is a common loss function used for regression problems. Evaluation metrics for regression is a Mean Absolute Error (MAE...