Socure’s patented AI-based identity bot, Aida, leapfrogs legacy approaches by continuously exploring live digital data, correlating thousands of identity data points online and offline, and then using the power of machine learning (ML) to create a holistic, accurate customer identity model. Through automation and the elimination of human intervention, Aida can produce more effective models as quickly as fraud can reshape itself.
In the upcoming six-part webinar series, Pablo Abreu, Socure’s VP of Data Science, will share his perspective on best practices for building, operating and maintaining an end-to-end AI-based machine learning bot.
Feature Engineering is what separates good machine learning outcomes from great machine learning outcomes. Part art and part science, feature engineering combines domain expertise with data science acumen to transform raw data into the variables that drive machine learning models.
In this second webinar in our six-part series, Socure’s VP Data Science, Pablo Abreu, discusses the methods used in feature engineering to go from raw data (discussed here Data Exploration - Improving the Foundation) to highly predictive features. More specifically, Pablo will share the approach
In this webinar, Pablo will share:
In this first of six webinars, Pablo starts at the beginning and discusses different methods for data exploration. As the goal of data science is to extract knowledge and insights from data, it makes sense that we start with data and explain the process used for the initial analysis of data.
In this on-demand webinar, Pablo shares: