Describes computational methods for parametric and nonparametric modeling of stochastic dynamics. Aimed at graduate students, and suitable for self-study.

Combining scientific computing methods and algorithms with modern data analysis techniques, including basic applications of compressive sensing and machine lear

A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.

Trains researchers and graduate students in state-of-the-art statistical and machine learning methods to build models with real-world data.

Computational and Data-Driven Chemistry Using Artificial Intelligence: Volume 1: Fundamentals, Methods and Applications highlights fundamental knowledge and cur