bayesian models

The Essential Book of AI - (Sirius Concepts) by Anne Rooney (Hardcover)

Mental Models - by Peter Hollins (Hardcover)

Active Machine Learning with Python - by Margaux Masson-Forsythe (Paperback)

JMP for Mixed Models - by Ruth Hummel & Elizabeth a Claassen & Russell D Wolfinger (Hardcover)

The Improbability Principle - by David J Hand (Paperback)

SAS for Dummies - 3rd Edition by Chris Hemedinger (Paperback)

Algorithms for the People - by Josh Simons

SPSS Statistics for Dummies - 4th Edition by Jesus Salcedo & Keith McCormick (Paperback)

Statistical Inference - (Dover Books on Mathematics) by Robert B Ash (Paperback)

Monte Carlo Principles and Neutron Transport Problems - (Dover Books on Mathematics) by Jerome Spanier & Ely M Gelbard (Paperback)

Graph Neural Networks in Action - (In Action) by Keita Broadwater & Namid Stillman (Paperback)

Financial Modelling Using Dynamic Arrays - by Liam Bastick (Paperback)

R All-In-One for Dummies - by Joseph Schmuller (Paperback)

Introduction to Meta-Analysis - 2nd Edition by Michael Borenstein & Larry V Hedges & Julian P T Higgins & Hannah R Rothstein (Hardcover)

Summary and Analysis of the Signal and the Noise: Why So Many Predictions Fail--But Some Don't - (Smart Summaries) by Worth Books (Paperback)

GMAT Official Guide Data Insights Review 2026 - 2027 - (Paperback)

Machine Learning for Dummies - 3rd Edition by Luca Massaron (Paperback)

Machine Learning with Quantum Computers - (Quantum Science and Technology) 2nd Edition by Maria Schuld & Francesco Petruccione

Grokking Deep Learning - by Andrew Trask (Paperback)

The Essential Book of Useless Information - by Don Voorhees (Paperback)

The Means of Prediction - by Maximilian Kasy (Hardcover)

Machine Learning Algorithms in Depth - by Vadim Smolyakov (Paperback)

Causal AI - by Robert Osazuwa Ness (Paperback)

Generative Ai: The Insights You Need from Harvard Business Review - (HBR Insights) (Paperback)