InfoQ Homepage Presentations Validation Methodology of Large Unstructured Unsupervised Learning Systems
Validation Methodology of Large Unstructured Unsupervised Learning Systems
25:32
Summary
Lawrence Chernin describes best practices and validation methods used to deal with large unstructured data, including a suite of unit tests covering the implementations of algorithmic equations.
Bio
Lawrence Chernin has worked in the data science field for six years. Prior to data science he worked in the semiconductor software field for many years and originally worked as an astrophysicist at Berkeley. He has a PhD from Harvard University and is an Kaggle enthusiast.
About the conference
Managing Big Data has become a major competitive advantage for many organizations and hence maintaining a proper analytics platform is vital for an organization's survival. This conference provides insights and potential solutions to address Big Data issues from well known experts and thought leaders through panel sessions and open Q&A sessions.
Nov 26, 2016