Multi-Variate Feature Engineering Presentation for Machine Learning

Explore multi-variate feature engineering techniques for machine learning in this concise presentation from the Society of Actuaries Predictive Analytics Symposium 2019. Delve into feature importance, the necessity of feature engineering, and why models struggle with extrapolation. Discover the types of features that most models cannot engineer independently. Cover topics such as feature ranking, target coding, neural networks, and embedding layers. Gain insights into improving model performance through effective feature engineering strategies.

Introduction
Feature Engineering
Math Test for Models
Results
Target Coding
Neural Networks
Embedding Layers
Feature Ranking