Machine Learning Refined

Introduction to Transfer Learning: Algorithms and Practice (Machine Learning: Foundations, Methodologies, and Applications)

Optimal Input Signals for Parameter Estimation

An Introduction to Statistical Modelling

Probability and Random Processes with One Thousand Exercises in Probability

Probabilistic Combinatorial Optimization on Graphs

Advanced Markov Chain Monte Carlo Methods Learning from Past Samples

An Introduction to Statistical Computing A Simulation-based Approach

Machine Learning (McGraw-Hill International Editions Computer Science Series)

Machine Learning: An Algorithmic Perspective, Second Edition (Chapman & Hall/CRC Machine Learning & Pattern Recognition)

Applied Probability Models With Optimization Applications

Machine Learning: Theory and Practice M. N. Murty [New] [Softcover]

Fundamentals of Machine Learning for Predictive Data Analytics, second edition: Algorithms, Worked Examples, and Case Studies

Probability, Random Variables, Statistics, and Random Processes Fundamentals & Applications

Statistical Models (Cambridge Series in Statistical and Probabilistic Mathematics, Series Number 11)

A First Course in Probability and Markov Chains

Probability and Stochastic Modeling

Bayesian Statistics : An Introduction

Seeing Through Statistics

Probabilistic Machine Learning for Finance and Investing: A Primer to Generative AI with Python

Probability Theory and Statistical Inference

Basic Probability Theory