DAMA Day 2018 | Building and Deploying Predictive Models with Dean Abbott
Event Information
Description
Building and Deploying Predictive Models
October 18th, 2018
a full-day training event with Dean Abbott
by DAMA - Portland Metro Chapter
sponsored by WhereScape
The DAMA Portland Chapter Board, in conjunction with our sponsors WhereScape, are proud to welcome back one of our most popular speakers, Dean Abbott of Abbott Analytics. For this year’s DAMA Day, Dean will focus on Data Science: Building and deploying predictive models.
This is an amazing value for your training budget, especially if you are looking for exposure to data science and how to apply predictive modeling to your business use-cases. Follow @damapdx on Twitter and watch this event page for the latest updates.
About the Speaker
Dean Abbott has over 21 years of experience applying advanced data mining, data preparation, and data visualization methods in real-world data intensive problems. In addition, Dean has developed and evaluated algorithms for use in commercial data mining and pattern recognition products, including polynomial networks, neural networks, radial basis functions, and clustering algorithms. Dean is a seasoned instructor, having taught a wide range of data mining tutorials and seminars. He is the instructor of well-regarded data mining courses, explaining concepts in language readily understood by a wide range of audiences, including analytics novices, data analysts, statisticians, and business professionals. Dean has also has taught both applied and hands-on data mining courses for a number of large software vendors.
Dean is planning to present four progressive sessions covering the building and deployment of predictive models. The sessions will include demos, and Dean prefers a largely interactive format allowing plenty of time for Q&A both during the sessions and at the end of the day.
When
Thursday, October 18th, 2018
Full day's schedule posted at DAMAPDX.org
Where
Standard Insurance Building, downtown Portland
Cost
$49 members (or employees of corporate members)
$69 non-members
See our corporate members