Rahul is a final year student pursuing his Bachelors in Computer Science and Engineering from The LNM Institute of Information Technology, Jaipur, India. He is a self taught Data Scientist and Full Stack Web Developer, always open to learn new stuff. He is enthusiastic on making Machine Learning more transparent and interpretable for everyone.
Topic: Visualize the Black Box – An introduction to Interpretable Machine Learning.
What’s the use of machine learning models if we can’t interpret them? This session will cover recent model interpretability techniques that are essential for Data Scientist to have in their toolbox. Attendees will learn how to apply these techniques in Python on a real-world data science problem. It will start with an introduction to what is Machine Learning interpretability and why is it necessary for Data Scientists. They will learn the value it brings to any Data Science project/real-world business problem. It will also discuss industries where model interpretability is extremely important. Finally, the talk will run through a live example to make things absolutely clear.
Targeting audience with advanced level of Python knowledge.