Human and Machine Learning: Visible, Explainable, Trustworthy and Transparent (Zhou Jianlong)(Pevná vazba)

Human and Machine Learning: Visible, Explainable, Trustworthy and Transparent (Zhou Jianlong)(Pevná vazba)

Part I Transparency in Machine Learning.- Part II Visual Explanation of Machine Learning Process.- Part III Algorithmic Explanation of Machine Learning Models.- Part IV User Cognitive Responses in ML-Based Decision Making.- Part V Human and Evaluation of Machine Learning.- Part VI Domain Knowledge

Machine Learning (Zhou Zhi-Hua)(Pevná vazba)

Part 3 (Chapters 11-16) introduces some advanced topics, covering feature selection and sparse learning, computational learning theory, semi-supervised learning, probabilistic graphical models, rule learning, and reinforcement

Hands-On Machine Learning with R (Boehmke Brad)(Pevná vazba)

Hands-on Machine Learning with R provides a practical and applied approach to learning and developing intuition into today's most popular machine learning methods. This book serves as a practitioner's guide to the machine learning process and is meant to help the reader learn to apply the machine

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

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

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

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

Natural Language Processing: A Machine Learning Perspective (Zhang Yue)(Pevná vazba)

With a machine learning approach and less focus on linguistic details, this gentle introduction to natural language processing develops fundamental mathematical and deep learning models for NLP under a unified framework. NLP problems are systematically organised by their machine learning nature,

Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning (Gilliland Michael)(Pevná vazba)

Discover the role of machine learning and artificial intelligence in business forecasting from some of the brightest minds in the field In Business Forecasting: The Emerging Role of Artificial Intelligence and Machine Learning accomplished authors Michael Gilliland, Len Tashman, and Udo Sglavo

A First Course in Machine Learning (Rogers Simon)(Pevná vazba)

'A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility, starts from a detailed explanation of the basic foundations of Bayesian analysis in the simplest of settings, and goes

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

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

Buddhism and Intelligent Technology: Toward a More Humane Future (Hershock Peter D.)(Paperback)

When machine learning, data and AI are reshaping the human experience and forcing us to develop a new ethical intelligence, Peter Hershock gives us a new way to think about attention, presence and ethics in our changing lives by balancing Western technology with Asian philosophy. Rather than

I Am Love: A Book of Compassion (Verde Susan)(Pevná vazba)

Companion to I Am Human and I Am Peace 'Practical and empowering for young ones learning how to emotionally attend to themselves and others.' --Kirkus Reviews Celebrate kindness, compassion, self-care, and love in all its forms in this beautifully illustrated book! Love means showing kindness,

Gaussian Processes for Machine Learning (Rasmussen Carl Edward)(Pevná vazba)

A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines.Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received

Machine Learning Control - Taming Nonlinear Dynamics and Turbulence (Duriez Thomas)(Pevná vazba)

This is the first textbook on a generally applicable control strategy for turbulence and other complex nonlinear systems. The approach of the book employs powerful methods of machine learning for optimal nonlinear control laws. This machine learning control (MLC) is motivated and detailed in

Human Body (Brundle Joanna)(Pevná vazba)

Discover and Learn is a visually stimulating series that explores core areas of learning. This series uses eye-catching imagery, informative diagrams and fascinating facts to bring key subject areas to

Wedges (Rustad Martha E. H.)(Pevná vazba)

Beginner readers and budding young scientists will love learning about using simple machines in everyday situations. Along the way, readers will be supported by expertly levelled text, a strong text-photo match and appropriate text load. Readers will be excited to dig in and learn all about simple

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

Screws (Rustad Martha E. H.)(Pevná vazba)

Beginner readers and budding young scientists will love learning about using simple machines in everyday situations. Along the way, readers will be supported by expertly levelled text, a strong text-photo match and appropriate text load. Readers will be excited to dig in and learn all about simple

Sensation Machines (Wilson Adam)(Pevná vazba)

A razor-sharp, darkly funny, and deeply human rendering of a Post-Trump America in economic free fall Michael and Wendy Mixner are a Brooklyn-based couple whose marriage is failing in the wake of a personal tragedy. Michael, a Wall Street trader, is meanwhile keeping a secret: he lost the couple's

Inclined Planes (Rustad Martha E. H.)(Pevná vazba)

Beginner readers and budding young scientists will love learning about using simple machines in everyday situations. Along the way, readers will be supported by expertly levelled text, a strong text-photo match and appropriate text load. Readers will be excited to dig in and learn all about simple

Learning and Memory (Gluck Mark A.)(Pevná vazba)

Human Rights and Liberty (Ogden Charlie)(Pevná vazba)