bayesian models

Biomathematical Modeling - (De Gruyter Textbook) by Olcay Akman & Christopher Hay-Jahans (Paperback)

Analysis and Probability - (Elsevier Insights) by Aurel Spataru (Hardcover)

Multiparametric Statistics - by Vadim Ivanovich Serdobolskii (Hardcover)

A First Course in Bayesian Statistical Methods - (Springer Texts in Statistics) by Peter D Hoff

Introduction to Transfer Learning - (Machine Learning: Foundations, Methodologies, and Applications) by Jindong Wang & Yiqiang Chen (Paperback)

Biostatistics Using JMP - by Trevor Bihl (Paperback)

Data-Centric Machine Learning with Python - by Jonas Christensen & Nakul Bajaj & Manmohan Gosada (Paperback)

Linear Algebra and Optimization for Machine Learning - 2nd Edition by Charu C Aggarwal (Hardcover)

Machine Learning and AI with Simple Python and MATLAB Scripts - (IEEE Press) by M Umit Uyar (Hardcover)

Basic Statistics for Life Scientists - by Jakub Tomek (Hardcover)

Multifaceted Uncertainty Quantification - (De Gruyter Stem) by Isaac Elishakoff (Paperback)

Machine Learning Concepts with Python and the Jupyter Notebook Environment - by Nikita Silaparasetty (Paperback)

Rearchitecting Llms - by Pere Martra (Paperback)

Nonparametric Functional Data Analysis - (Springer Statistics) by Frédéric Ferraty & Philippe Vieu (Hardcover)

Building Regression Models with SAS - by Robert N Rodriguez (Paperback)

Bayesian and Frequentist Regression Methods - (Springer Statistics) by Jon Wakefield (Hardcover)

Structural Equation Modeling - (Quantitative Methods in Education and the Behavioral Science) 2nd Edition by Gregory R Hancock & Ralph O Mueller

Convex Optimization for Machine Learning - by Changho Suh (Hardcover)

Quantum Computing and Quantum Machine Learning for Engineers and Developers - by Jesse Van Griensven Thé & Roydon Andrew Fraser & Jose Rosas-Bustos