Speaker "Kevin Sun" Details Back



Practical Data Science - An Overview of Data Science Best Practices for Common Business Problems


This talk will provide a framework to help you decide what data science techniques are appropriate for your business problem. A comparison of various data science algorithms will be covered, along with their trade-offs, and examples of business use cases. This talk with also cover the bias-variance trade-off error and how to account for this in your models. Additionally, topics on how to deal with common data problems - such as missing data and too many predictors - will be covered.


Kevin Sun is a data scientist for the talent analytics team at Deloitte. His work involves leveraging internal and external data to help business leaders gain a better understanding of ways to improve Deloitte’s workforce. Prior to joining Deloitte, he worked with the Center for Brain Immunology and Glia at University of Virginia to design a ML algorithm that discovers novel gene sets predictive of cell types. His side interests include NBA analytics, stock analytics, and natural language processing. He received his Master Degree in Data Science at University in Virginia