Good, Fast, Cheap - How to Do Data Science with Missing Data
Explore effective strategies for handling missing data in data science projects through this comprehensive workshop session. Learn to visualize missing data and identify three distinct types, understanding their impact on decision-making processes. Discover the advantages and disadvantages of avoiding, ignoring, or accounting for missing data, and gain practical implementation techniques for each approach. Acquire valuable tips for integrating missing data handling into your workflow, balancing the trade-offs between good, fast, and cheap solutions. Benefit from the expertise of Matthew Brems, an award-winning data scientist with experience across various industries, as he guides you through this critical aspect of data analysis and machine learning.