Computer Science and Intelligent Systems

An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives.

An introduction to the engineering principles of embedded systems, with a focus on modeling, design, and analysis of cyberphysical systems.

The gap between theoretical ideas and messy reality, as seen in Neal Stephenson, Adam Smith, and Star Trek.

An introduction to algorithms for readers with no background in advanced mathematics or computer science, emphasizing examples and realworld problems.

What artificial intelligence can tell us about the mind and intelligent behavior.

Tamir HazanGeorge Papandreou
A description of perturbationbased methods developed in machine learning to augment novel optimization methods with strong statistical guarantees.

The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization.

The first textbook to teach students how to build data analytic solutions on large data sets using cloudbased technologies.

A textbook that teaches students to read and write proofs using Athena.

Formal ways of representing uncertainty and various logics for reasoning about it; updated with new material on weighted probability measures, complexitytheoretic considerations, and other topics.

Tamir HazanGeorge Papandreou