This is a sequential model I built to predict the values of income based on selected features
for preprocessing I used a mix of:
-One hot encoding
-Back-fill/mean-fill of missing values
-irrelevant feature pruning
-Data visualisation (initData.html and initDataProcessed.html)
-Outlier removal
-feature normalization
Model: I used Keras Sequential model with 3 layers two of which had 64 nodes and third have 32 nodes, an adam optimizer and an early callback with a patience of 10 epochs.
I would like to give credit to this tutorial as it gave me great insight on how to build the model: https://www.tensorflow.org/tutorials/keras/regression
I achived a RSME of 61,234 on my final submission.