Step-by-Step Guide to Build Interpretable Machine Learning Model -Python

Can you interpret a deep neural network? Building a complex and dense machine learning model has the potential of reaching our desired accuracy, but does it make sense? Can you open up the black-box model and explain how it arrived at the final result? These are critical questions we need to answer as data scientists. A wide variety of businesses are relying on machine learning to drive their strategy and spruce up their bottomline. Building a model that we can explain to our clients and stakeholders is key.