For September, we are delighted to have DataRobot to share on how Statisticians and Data Scientists can complement, and learn important practices from each other.
Title: How Statisticians and Data Scientists could learn from each other
Data Scientists have been highly successful at automating modeling through Machine learning, and continue to build capabilities to extract powerful insights at an impressive pace.
On the other hand, Statisticians have been attempting to manually build complex and robust models with features from Generalized Linear Models (GLMs), such as p-values, exponential distributions, link functions, offsets and mixed models.
These GLMs functions are little-known by Data Scientists while Statisticians may dismiss Machine Learning tools that they find too complex, calling them “black boxes”.
Are Statisticians missing something here that could present important opportunities to help them find patterns and build solutions for the increasingly larger and more complex ranges of data?
This presentation will show that Statisticians and Data Scientists can complement, and learn important practices from each other.
The Xgboost package, one of the most popular open source projects, is a good example of such collaboration.
But more can be done. We will mention as examples some Datarobot projects that combine tricks from the two communities. We will also see that researchers in actuarial science in Japan and Europe show strong interest in sophisticated Regularized GLMs that are still unused by both communities.
Xavier Conort is the Chief Data Scientist for DataRobot, where he leads the R&D efforts in Data Science globally from Singapore. Xavier is passionate about extracting value and insight from data and has applied Machine Learning to diverse business problems ranging from churn prediction to claims modeling, flight arrival prediction, essay scoring, sales forecasting, and biological response prediction. Before joining DataRobot, Xavier was principal research engineer in I2R and has an extensive experience in the insurance industry as an actuary in France, Brazil, China and Singapore. To help his conversion into Data Science and sharpen his skills in Machine Learning, Xavier competed on Kaggle and in KDDCups where he won 10 prizes and was the #1 ranked data scientist on Kaggle in 2012-2013.
- 1830 - 1900: Networking [casual; small talk]
- 1900 - 2030: Sharing by DataRobot [core]
NTUC Auditorium, Level 7
1 Marina Boulevard
- Opens: 05 Sep 2018 (Wed), 08:00 PM
- Closes: 18 Sep 2018 (Tue), 06:00 PM
Please note of our new attendance policy (https://www.meetup.com/DataScience-SG-Singapore/events/228169542/). Attendees are REQUIRED to RSVP to the event to be allowed into the venue. People who are neither in the "going" nor "wait" lists will be turned away. Please be considerate and update your RSVP if you are not able to make it.