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The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice.
Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning,
The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice.Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data
Despite the recent rapid growth in machine learning and predictive analytics, many of the statistical questions that are faced by researchers and practitioners still involve explaining why something is happening. Regression analysis is the best 'swiss army knife' we have for answering these kinds
This updated second edition offers a guided tour of machine learning algorithms and architecture design. It provides real-world applications of intelligent systems in healthcare and covers the challenges of managing big data.The book has been updated with the latest research in massive data,
This book describes in detail the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal processing, two of the most important and exciting technologies in the modern information economy. Taking a gradual approach, it builds up concepts in a
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 new edition of a guide to distributed algorithms that emphasizes examples and exercises rather than the intricacies of mathematical models.This book offers students and researchers a guide to distributed algorithms that emphasizes examples and exercises rather than the intricacies of
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: A Bayesian and Optimization Perspective, Second Edition gives a unifying perspective on machine learning by covering both probabilistic and deterministic approaches based on optimization techniques combined with the Bayesian inference approach. The book builds from the basic
Terrorism and WMD's, Second Edition provides a comprehensive, up-to-date survey of terrorism and weapons of mass destruction (WMDs). Terrorist weapons and delivery methods are becoming increasingly sophisticated; as such, this book focuses on the chemistry and biology of WMDs, the development and
A book at the intersection of data science and media studies, presenting concepts and methods for computational analysis of cultural data. How can we see a billion images? What analytical methods can we bring to bear on the astonishing scale of digital culture--the billions of photographs shared on
A comprehensive survey of artificial intelligence algorithms and programming organization for robot systems, combining theoretical rigor and practical applications.This textbook offers a comprehensive survey of artificial intelligence (AI) algorithms and programming organization for robot systems
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,
Featuring numerous case examples from companies around the world, this second edition integrates theoretical advances and empirical data with practical applications, including in-depth discussion on the COBIT 5 framework which can be used to build, measure and audit enterprise governance of IT
'Refreshingly thought-provoking...' - The Financial Times The essential playbook for the future of your business What To Do When Machines Do Everything is a guidebook to succeeding in the next generation of the digital economy. When systems running on Artificial Intelligence can drive our cars,
A post-apocalyptic science fiction tale of a woman, and her cat, in search of a powerful machine. A Second Edition of the hit graphic novel by the creator of Head Lopper. This second edition hardcover includes more story, a new cover and process material never seen before. Alone at the end of the
During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the
In one volume for the first time, this revised and updated examination of how J.R.R.Tolkien came to write his original masterpiece The Hobbit includes his complete unpublished draft version of the story, together with notes and illustrations by Tolkien himself. The Hobbit was first published on 21