bayesian models

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

Google Bigquery: The Definitive Guide - by Valliappa Lakshmanan & Jordan Tigani (Paperback)

Let the Evidence Speak - by Alan Jessop (Paperback)

Time Series Analysis with Python Cookbook - Second Edition - 2nd Edition by Tarek A Atwan (Paperback)

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

Thoughtful Data - (Paperback)

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

Statistics Using Python - by Oswald Campesato (Paperback)

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

Beginning Anomaly Detection Using Python-Based Deep Learning - 2nd Edition by Suman Kalyan Adari & Sridhar Alla (Paperback)

Deep Learning with Pytorch, Second Edition - by Luca Antiga & Eli Stevens & Howard Huang & Thomas Viehmann (Paperback)

Building Large Language Models from Scratch - by Dilyan Grigorov (Paperback)

Rearchitecting Llms - by Pere Martra (Paperback)

Machine Learning for Dummies - 3rd Edition by Luca Massaron & John Paul Mueller (Paperback)

Nonstandard Methods in Stochastic Analysis and Mathematical Physics - (Dover Books on Mathematics) (Paperback)

The Means of Prediction - by Maximilian Kasy (Hardcover)

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

Timeless Algorithms, the Foundational Ideas - by Gary Sutton (Paperback)

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

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

Practitioner's Knowledge Representation - by Emilia Mendes (Hardcover)

Gamechanger AI - by Klaus Henning (Paperback)

Microsoft Dynamics 365 AI for Business Insights - by Dmitry Shargorodsky (Paperback)

Pattern Recognition and Machine Learning - (Information Science and Statistics) by Christopher M Bishop (Hardcover)