Information Theory, Inference and Learning Algorithms (MacKay David J. C.)(Pevná vazba)

Information Theory, Inference and Learning Algorithms (MacKay David J. C.)(Pevná vazba)

Information theory and inference, often taught separately, are here united in one entertaining textbook. These topics lie at the heart of many exciting areas of contemporary science and engineering - communication, signal processing, data mining, machine learning, pattern recognition, computational

Elements of Causal Inference: Foundations and Learning Algorithms (Peters Jonas)(Pevná vazba)

A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning.The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a

Data Mining and Machine Learning: Fundamental Concepts and Algorithms (Zaki Mohammed J.)(Pevná vazba)

The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business analytics. This textbook for senior undergraduate and

Computer Vision (Prince Simon J. D.)(Pevná vazba)

This modern treatment of computer vision focuses on learning and inference in probabilistic models as a unifying theme. It shows how to use training data to learn the relationships between the observed image data and the aspects of the world that we wish to estimate, such as the 3D structure or the

The Machine Learning: A Probabilistic Perspective (Murphy Kevin P.)(Pevná vazba)

A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns

Motivation and Foreign Language Learning - From theory to practice(Pevná vazba)

Poems That Solve Puzzles: The History and Science of Algorithms (Bleakley Chris)(Pevná vazba)

Algorithms are the hidden methods that computers apply to process information and make decisions. Nowadays, our lives are run by algorithms. They determine what news we see. They influence which products we buy. They suggest our dating partners. They may even be determining the outcome of national

Information-Driven Planning and Control (Ferrari Silvia)(Pevná vazba)

A unified framework for developing planning and control algorithms for active sensing, with examples of applications for specific sensor technologies. Active sensor systems, increasingly deployed in such applications as unmanned vehicles, mobile robots, and environmental monitoring, are

Handbook of Game-Based Learning (Plass Jan L.)(Pevná vazba)

A comprehensive introduction to the latest research and theory on learning and instruction with computer games.This book offers a comprehensive introduction to the latest research on learning and instruction with computer games. Unlike other books on the topic, which emphasize game development or

Examples in Parametric Inference with R (Dixit Ulhas Jayram)(Pevná vazba)

This book discusses examples in parametric inference with R. Combining basic theory with modern approaches, it presents the latest developments and trends in statistical inference for students who do not have an advanced mathematical and statistical background. The topics discussed in the book are

Machine Learning Refined: Foundations, Algorithms, and Applications (Watt Jeremy)(Pevná vazba)

With its intuitive yet rigorous approach to machine learning, this text provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the

Prediction, Learning, and Games (Cesa-Bianchi Nicolo)(Pevná vazba)

This important text and reference for researchers and students in machine learning, game theory, statistics and information theory offers a comprehensive treatment of the problem of predicting individual sequences. Unlike standard statistical approaches to forecasting, prediction of individual

Bandit Algorithms (Lattimore Tor)(Pevná vazba)

Decision-making in the face of uncertainty is a significant challenge in machine learning, and the multi-armed bandit model is a commonly used framework to address it. This comprehensive and rigorous introduction to the multi-armed bandit problem examines all the major settings, including

Experiential Learning: Experience as the Source of Learning and Development (Kolb David)(Pevná vazba)

&a>Experiential learning is a powerful and proven approach to teaching and learning that is based on one incontrovertible reality: people learn best through experience. Now, in this extensively updated book, David A. Kolb offers a systematic and up-to-date statement of the theory of experiential

Algorithms for Optimization (Kochenderfer Mykel J.)(Pevná vazba)

A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems.This book offers a comprehensive introduction to optimization with a focus on practical algorithms. The book approaches optimization from an engineering perspective, where the

Fundamentals of Quantum Computing: Theory and Practice (Kasirajan Venkateswaran)(Pevná vazba)

This introductory book on quantum computing includes an emphasis on the development of algorithms. Appropriate for both university students as well as software developers interested in programming a quantum computer, this practical approach to modern quantum computing takes the reader through the

Statistical Inference (Casella George)(Pevná vazba)

This book builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of

Introduction to Machine Learning with Applications in Information Security (Stamp Mark)(Pevná vazba)

Introduction to Machine Learning with Applications in Information Security provides a class-tested introduction to a wide variety of machine learning algorithms, reinforced through realistic applications. The book is accessible and doesn't prove theorems, or otherwise dwell on mathematical theory

Principles of Robot Motion: Theory, Algorithms, and Implementations (Choset Howie)(Pevná vazba)

A text that makes the mathematical underpinnings of robot motion accessible and relates low-level details of implementation to high-level algorithmic concepts.Robot motion planning has become a major focus of robotics. Research findings can be applied not only to robotics but to planning routes on

Management Information Systems (Sousa Ken J.)(Pevná vazba)

Drawing from the latest developments and practices from the field, MANAGEMENT INFORMATION SYSTEMS, 7e combines a wealth of case studies and real-world examples to provide a clear emphasis on the business and management elements of information technology. The new edition offers the most current

Blended Learning in Practice: A Guide for Practitioners and Researchers (Madden Amanda G.)(Pevná vazba)

A guide to both theory and practice of blended learning offering rigorous research, case studies, and methods for the assessment of educational effectiveness.Blended learning combines traditional in-person learning with technology-enabled education. Its pedagogical aim is to merge the scale,

Category Theory for the Sciences (Spivak David I.)(Pevná vazba)

An introduction to category theory as a rigorous, flexible, and coherent modeling language that can be used across the sciences.Category theory was invented in the 1940s to unify and synthesize different areas in mathematics, and it has proven remarkably successful in enabling powerful

Foundations of Machine Learning, Second Edition (Mohri Mehryar)(Pevná vazba)

A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms.This book is a general introduction to machine learning that can serve as a textbook for graduate students and a reference for researchers. It covers fundamental modern topics in

Bayesian Reasoning and Machine Learning (Barber David)(Pevná vazba)

Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who