|Where:||Join us from anywhere!|
|Cost:||Free—but registrations are limited|
We are faced with more and more data, often with many, and poorly described or understood, variables. We can even have more variables than we do data. Classical techniques break down when applied to such data.
Lasso and elastic net are two popular machine-learning methods designed to sift through these kinds of data and extract features that have the ability to predict outcomes.
Join Di Liu, Senior Econometrician and developer at StataCorp, as he introduces Stata 16's new features for lasso and elastic net. In this webinar, Di will demonstrate how lasso and elastic net can be used for prediction with linear, binary, and count outcomes. Discover why these methods are effective and how they work.
The webinar is free, but you must register to attend. Registrations are limited, so register soon. Register by clicking the desired date of your course above.
We will send you an email prior to the start of the course with instructions on how to access the webinar. You will need access to Adobe Connect to attend.
Don't miss this opportunity to see Stata's new lasso and elastic net features from the experts.
Di Liu is a Senior Econometrician at StataCorp He has a PhD degree in economics from Concordia University in Montreal, Canada; an engineer's degree in software engineering and statistics from Polytech'Lille in Lille, France; and master's and bachelor's degrees in computer science from Hohai University in Nanjing, China. His research interests lie in econometrics and computational methods.