As we progress into 2025, Artificial Intelligence (AI) continues to reshape industries and revolutionize how we interact with ...

This chapter is an introduction to regression and procedures for finding the best curve to fit a set of data. We will discuss linear and parabolic regression, and regression with power series ...

the time it takes to run 1.5 miles, and the heart rate while running. Thus, in order to predict oxygen consumption, you estimate the parameters in the following multiple linear regression equation: ...

All the frequently used numerical methods in physics are explained ... derivative-free optimization, Bayesian linear regression, neural networks, and partial differential equations. The last section ...

This book develops the theory of Tikhonov regularization for a certain class of linear inverse problems which are defined on Hilbert spaces. To explain why and how Tikhonov regularization works, the ...

This course covers nonparametric modeling of complex, nonlinear predictive relationships in data with categorical (classification) and numerical (regression) response variables. It is a follow-up ...