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Cambridge Handbook of Artificial Intelligence

The Cambridge handbook of artificial intelligence

Perception as Bayesian inference

Neural network learning: theoretical foundations

Algebraic geometry and statistical learning theory

Twitter: a digital socioscope

Statistical Methods for Recommender Systems

Statistical methods for recommender systems

Logic and algebraic structures in quantum computing : 45

Knowledge engineering: building personal learning assistants for evidence-based reasoning

The Theory of Quantum Information

Algorithmic Aspects of Machine Learning

Fundamentals of Computer Vision

Algorithmic aspects of machine learning

Fundamentals of computer vision

Measure of All Minds: Evaluating Natural and Artificial Intelligence

The measure of all minds: evaluating natural and artificial intelligence

Darkweb cyber threat intelligence mining

Turing's imitation game: conversations with the unknown

The Science of Deep Learning

Mathematics for Machine Learning

Control Systems and Reinforcement Learning

Machine Learning: A First Course for Engineers and Scientists

Wireless AI: Wireless Sensing, Positioning, IoT, and Communications

An introduction to multiagent systems

Adversarial Learning and Secure AI

A Hands-on Introduction to Data Science

Introduction to property testing

Data mining for business analytics: concepts, techniques, and applications with JMP Pro

Data mining: concepts, models, methods, and algorithms

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