Explains the core theory behind linear regression models, a fundamental machine learning algorithm for predicting continuous numerical values.
A theoretical introduction to Linear Regression models, explaining their use for predicting continuous variables and importance in interpretable fields like lending.
A high-level guide to tools and methods for understanding AI/ML models and their predictions, known as Explainable AI (XAI).
Explains the theory behind Linear Regression, a fundamental machine learning model for predicting continuous numerical values.
A crash course on the theory behind linear regression models, a fundamental machine learning algorithm for predicting numerical values.
Explores how uncertainty estimation in deep neural networks can be used for model interpretation, debugging, and improving reliability in high-risk applications.
Explores the importance of interpreting ML model predictions, especially in regulated fields, and reviews methods like linear regression and interpretable models.
