Exploratory Data Analysis (EDA) in Machine Learning - ML 075

EDA is primarily used in machine learning to see what data can reveal beyond the formal modeling or hypothesis testing task and provides a better understanding of data set variables and the relationships between them. It can also help determine if the statistical techniques you are considering for data analysis are appropriate. Today on the show, Ben and Michael discuss how to use EDA in machine learning models. In this episode...What is EDA?Tips and Tricks and steps for EDAHow to approach downsamplingUnderstanding feature sets relative to your labelsOptimizing modelsMotivating yourself to get into the dataTools for EDAA few scenarios for discussionWhat is the most detrimental EDA mistake for MLSponsorsTop End DevsCoaching | Top End DevsAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacyBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.