Human Interpretable Machine Learning (Part 1) -- The Need and Importance of Model Interpretation

Thanks to all the wonderful folks at DataScience.com and especially Pramit Choudhary for helping me discover the amazing world of model interpretation. The field of Machine Learning has gone through some phenomenal changes over the last decade. Starting off as just a pure academic and research-oriented domain, we have seen widespread industry adoption across diverse domains including retail, technology, healthcare, science and many more. Rather than just running lab experiments to publish a research paper, the key objective of data science and machine learning in the 21st century has changed to tackling and solving real-world problems, automating complex tasks and making our life easier and better. More than often, the standard toolbox of machine learning, statistical or deep learning models remain the same.