Python data mining and machine learning in action

Now , a leader of Northwestern University's prestigious analytics program presents a fully-integrated treatment of both the business and academic elements of marketing applications in predictive analy

The two-volume proceedings, LNAI 9077 + 9078, constitutes the refereed proceedings of the 19th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2015, held in Ho Ch

The two-volume proceedings, LNAI 9077 + 9078, constitutes the refereed proceedings of the 19th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2015, held in Ho Ch

The current book is the first publication of a complete overview of machine learning methodologies for the medical and health sector. It was written as a training companion and as a must-read, not onl

Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining; it is the science of exploring large and complex bodies of data in order to discover

Are you curious about AI? All you need is a good understanding of the Scala programming language, a basic knowledge of statistics, a keen interest in Big Data processing, and this book!

This best practice guide to teaching in the further education and skills sector, and professional organisational learning contexts, examines the key concepts underpinning effective teaching and learni

This best practice guide to teaching in the further education and skills sector, and professional organisational learning contexts, examines the key concepts underpinning effective teaching and learni

Along with updating all chapters and Python code examples, the second edition of this bestseller includes new chapters on Gaussian processes, Boltzmann machines, and deep belief networks. It also revi

With a focus on the needs of educators and students, Making Sense of Data presents the steps and issues that need to be considered in order to successfully complete a data analysis or data mining proj

"In an educational context where school and district performance is of increasing focus, it's essential for leaders at all levels of the educational system to focus on improving student performance. T

"This book highlights contemporary findings in the area of biologically-inspired techniques in data mining domains and their implementation in real-life problems"--

R is a powerful language for statistical computing and graphics that can handle virtually any data-crunching task. It runs on all important platforms and provides thousands of useful specialized modu

Data mining is well on its way to becoming a recognized discipline in the overlapping areas of IT, statistics, machine learning, and AI. Practical Data Mining for Business presents a user-friendly ap

"In an educational context where school and district performance is of increasing focus, it's essential for leaders at all levels of the educational system to focus on improving student performance. T

The book provides a description of the general underpinnings of mining along with the various mathematical and algorithmic methodologies that are incorporated in it. It describes the data management i

Machine learning and data mining are inseparably connected with uncertainty. The observable data for learning is usually imprecise, incomplete or noisy.Uncertainty Modeling for Data Mining: A Label Se

Owing to continuous advances in the computational power of handheld devices like smartphones and tablet computers, it has become possible to perform Big Data operations including modern data mining pr

Heutagogy, or self-determined learning, redefines how we understand learning and provides some exciting opportunities for educators. It is a novel approach to educational practice, drawing on familiar concepts such as constructivism, capability, andragogy and complexity theory. Heutagogy is also supported by a substantial and growing body of neuroscience research.Self-Determined Learning explores how heutagogy was derived, and what this approach to learning involves, drawing on recent research and practical applications. The editors draw together contributions from educators and practitioners in different fields, illustrating how the approach can been used and the benefits its use has produced. The subjects discussed include: the nature of learning, heutagogy in the classroom, flexible curriculum, assessment, e-learning, reflective learning, action learning and research, and heutagogy in professional practice settings.

Reinforcement learning (RL) is a framework for decision making in unknown environments based on a large amount of data. Several practical RL applications for business intelligence, plant control, and

Written for computer programming students, hobbyists, and professionals, FUNDAMENTALS OF PYTHON: DATA STRUCTURES is an introduction to object-oriented design and data structures using the popular Pyth

An effective guide to geographic information systems and remote sensing analysis using Python 3About This BookConstruct applications for GIS development by exploiting PythonThis focuses on built-in Py

This book reviews the latest techniques in exploratory data mining (EDM) for the analysis of data in the social and behavioral sciences to help researchers assess the predictive value of different com

This book reviews the latest techniques in exploratory data mining (EDM) for the analysis of data in the social and behavioral sciences to help researchers assess the predictive value of different com

Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning

Statistical learning and analysis techniques have become extremely important today, given the tremendous growth in the size of heterogeneous data collections and the ability to process it even from ph

The integration of machine learning techniques and cartoon animation research is fast becoming a hot topic. This book helps readers learn the latest machine learning techniques, including patch alignm

Tipping Points as evidenced in global events are, in many ways, influenced by media. DATA MINING for predicting and analyzing world events. This just released, ground-breaking book: DATAMINING: PREDIC

Based on expert observations of children who experience difficulties with maths this book gives a comprehensive overview of dyscalculia, providing a wealth of information and useful guidance for any p

Education scholars Baumfield (U. of Glasgow), Hall (Newcastle U.) and Wall (Durham U.) offer a guide for anyone who wants to find out more about the process of undertaking an enquiry into their profes

This volume directly addresses the complexities involved in data mining and the development of new algorithms, built on an underlying theory consisting of linear and non-linear dynamics, data selectio

Today's Web-enabled deluge of electronic data calls for automated methods of dataanalysis. Machine learning provides these, developing methods that can automatically detect patternsin data and then us

Vast amounts of data are nowadays collected, stored and processed, in an effort to assist in making a variety of administrative and governmental decisions. These innovative steps considerably improve

Computer vision is the science and technology of making machines that see. It is concerned with the theory, design and implementation of algorithms that can automatically process visual data to recogn

All too frequently we read that employers are singularly unimpressed with the skills set acquired by many pupils leaving formal education. Better problem solving, people skills, teambuilding and indep

This comprehensive volume presents the foundations of linear algebra ideas and techniques applied to data mining and related fields. Linear algebra has gained increasing importance in data mining and

If you’re an experienced programmer interested in crunching data, this book will get you started with machine learning—a toolkit of algorithms that enables computers to train themselves to automate us

Machine learning is an interdisciplinary field of science and engineering that studies mathematical theories and practical applications of systems that learn. This book introduces theories, methods and applications of density ratio estimation, which is a newly emerging paradigm in the machine learning community. Various machine learning problems such as non-stationarity adaptation, outlier detection, dimensionality reduction, independent component analysis, clustering, classification and conditional density estimation can be systematically solved via the estimation of probability density ratios. The authors offer a comprehensive introduction of various density ratio estimators including methods via density estimation, moment matching, probabilistic classification, density fitting and density ratio fitting, as well as describing how these can be applied to machine learning. The book provides mathematical theories for density ratio estimation including parametric and non-parametric conve

It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed “ensemble learning” by researchers in comp