Past Meetup

Myths of Data Science: Things you Should and Should Not Believe

This Meetup is past

13 people went

Price: $5.00 /per person

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The coffee is relatively informal and limited to only 25 people. The goal is to foster authentic conversations and build strong network for women in data. Light refreshments will be served.

There is no better way to grow yourself over a casual weekend coffee with like-minded data ladies! This time, we're excited to have Nina Zumel share her expertise on data science.

Myths of Data Science: Things you Should and Should Not Believe

Our most important data science tools are our theories and methods. In this talk, we will go back to fundamentals and look closely at some usually unexamined assumptions about statistics and machine learning.We will look at "myths" that arise in three common data scientist tasks: predictive modeling, analyzing the reliability or validity of results, and running controlled experiments (A/B testing). We will "debunk" these myths and offer some potential fixes to issues that can arise, all in a (hopefully) entertaining way.

More about Nina:

Dr. Nina Zumel is co-founder and principal at Win-Vector LLC, a data science consultancy based in San Francisco. She frequently writes and speaks on statistics and machine learning. She is also the co-author of the popular book Practical Data Science with R (Manning 2014), andis a frequent contributor to the Win-Vector Blog ( ). Nina has a degree in electrical engineering from UC Berkeley and a Ph.D. in robotics from Carnegie Mellon.


• 10:00- 10:30 Check-in & networking

• 10:30- 10:40 Quick introductions

• 10:40- 11:40 Speaker and Q&A

• 11:40- 12:30 Networking

All are welcome to attend, however, if a waitlist forms we may kindly ask for volunteers to relinquish their spots for women who wish to attend.

Code of Conduct: