As a data science group, we are no doubt enthusiasts of the various applications of data science to solve real world problems. However, with the hype around data science combined with the proliferation of easy to build DYI data science tools, it has become extremely easy for anyone to build a complex data science model. Many a folks new to data science, at times, fall into a few fallacies while interpreting the results. Just as powerful data can be, it can also be misleading. Not being aware of these fallacies could lead to drawing incorrect conclusions and poor decision making.
During the talk, the speaker Manas Bhat, will run us through a few cases of data science fallacies or errors that we need to watch out for while analyzing our data models including
• Sampling bias
• Data Dredging
• False Causality
• And a few others
Come attend the talk to know more!
About our Speaker
Manas Bhat is currently the Director of Strategy at Guitar Center where he assists in data driven decision making. Most of you already know him since he is one of the Co-Organizers of our Westlake Village Data Science meetup. He was one of the speakers at the 2017 Big Data Day LA conference that had over 3,000 attendees. Prior to joining Guitar Center, he worked at a management consulting firm Kurt Salmon where he built statistical models that drove business value. He also worked at two Fortune 500 engineering firms where he was involved with software development as well as process improvement through Six Sigma.