bayesian models

Information Theory and Statistics - (Dover Books on Mathematics) by Solomon Kullback (Paperback)

Introduction to Statistics with the Wolfram Language - by Juan H Klopper (Paperback)

Deep Generative Modeling - 2nd Edition by Jakub M Tomczak (Hardcover)

Statistics II for Dummies - 2nd Edition by Deborah J Rumsey (Paperback)

Retrieval Augmented Generation, the Seminal Papers - by Ben Auffarth (Paperback)

The Art of Modeling Dynamic Systems - (Dover Books on Computer Science) by Foster Morrison (Paperback)

How Large Language Models Work - by Edward Raff & Drew Farris & Stella Biderman (Paperback)

Principles and Theory for Data Mining and Machine Learning - (Springer Statistics) by Bertrand Clarke & Ernest Fokoue & Hao Helen Zhang

Grokking Statistics - by Thomas Nield (Paperback)

All of Statistics - (Springer Texts in Statistics) by Larry Wasserman (Hardcover)

Finite Markov Processes and Their Applications - (Dover Books on Mathematics) by Marius Iosifescu (Paperback)

Bayesian Biostatistics - (Statistics in Practice) by Emmanuel Lesaffre & Andrew B Lawson (Hardcover)

SAS for Mixed Models - by Walter W Stroup & George A Milliken & Elizabeth a Claassen (Hardcover)

Think Bayes - 2nd Edition by Allen B Downey (Paperback)

A Gentle Introduction to Statistics Using SAS Studio in the Cloud - by Ron Cody (Paperback)

How Algorithms Create and Prevent Fake News - by Noah Giansiracusa (Paperback)

Grokking Machine Learning, Second Edition - by Luis Serrano (Paperback)

Google Machine Learning and Generative AI for Solutions Architects - by Kieran Kavanagh (Paperback)

Reinforcement Learning - by D Phil Winder Ph (Paperback)

Fundamentals of Deep Learning - 2nd Edition by Nithin Buduma & Nikhil Buduma & Joe Papa (Paperback)

Data Science on the Google Cloud Platform - 2nd Edition by Valliappa Lakshmanan (Paperback)

Deep Learning for Time Series Cookbook - by Vitor Cerqueira & Luís Roque (Paperback)

Build a Reasoning Model (from Scratch) - (From Scratch) by Sebastian Raschka (Paperback)