WASABI

WASABI
Author: Christian Becker-Asano
Publisher: IOS Press
Total Pages: 208
Release: 2008
Genre: Artificial intelligence
ISBN: 9783898383196

I-ways

I-ways
Author:
Publisher:
Total Pages: 698
Release: 2006
Genre: Computer networks
ISBN:

Data Mining

Data Mining
Author: Thuc D. Le
Publisher: Springer Nature
Total Pages: 266
Release: 2019-11-22
Genre: Computers
ISBN: 9811516995

This book constitutes the refereed proceedings of the 17th Australasian Conference on Data Mining, AusDM 2019, held in Adelaide, SA, Australia, in December 2019. The 20 revised full papers presented were carefully reviewed and selected from 56 submissions. The papers are organized in sections on research track, application track, and industry showcase.

How Learning Works

How Learning Works
Author: Susan A. Ambrose
Publisher: John Wiley & Sons
Total Pages: 336
Release: 2010-04-16
Genre: Education
ISBN: 0470617608

Praise for How Learning Works "How Learning Works is the perfect title for this excellent book. Drawing upon new research in psychology, education, and cognitive science, the authors have demystified a complex topic into clear explanations of seven powerful learning principles. Full of great ideas and practical suggestions, all based on solid research evidence, this book is essential reading for instructors at all levels who wish to improve their students' learning." —Barbara Gross Davis, assistant vice chancellor for educational development, University of California, Berkeley, and author, Tools for Teaching "This book is a must-read for every instructor, new or experienced. Although I have been teaching for almost thirty years, as I read this book I found myself resonating with many of its ideas, and I discovered new ways of thinking about teaching." —Eugenia T. Paulus, professor of chemistry, North Hennepin Community College, and 2008 U.S. Community Colleges Professor of the Year from The Carnegie Foundation for the Advancement of Teaching and the Council for Advancement and Support of Education "Thank you Carnegie Mellon for making accessible what has previously been inaccessible to those of us who are not learning scientists. Your focus on the essence of learning combined with concrete examples of the daily challenges of teaching and clear tactical strategies for faculty to consider is a welcome work. I will recommend this book to all my colleagues." —Catherine M. Casserly, senior partner, The Carnegie Foundation for the Advancement of Teaching "As you read about each of the seven basic learning principles in this book, you will find advice that is grounded in learning theory, based on research evidence, relevant to college teaching, and easy to understand. The authors have extensive knowledge and experience in applying the science of learning to college teaching, and they graciously share it with you in this organized and readable book." —From the Foreword by Richard E. Mayer, professor of psychology, University of California, Santa Barbara; coauthor, e-Learning and the Science of Instruction; and author, Multimedia Learning

Neutrosophic soft sets forecasting model for multi-attribute time series

Neutrosophic soft sets forecasting model for multi-attribute time series
Author: Hongjun Guan
Publisher: Infinite Study
Total Pages: 21
Release:
Genre: Mathematics
ISBN:

Traditional time series forecasting models mainly assume a clear and definite functional relationship between historical values and current/future values of a dataset. In this paper, we extended current model by generating multi-attribute forecasting rules based on consideration of combining multiple related variables. In this model, neutrosophic soft sets (NSSs) are employed to represent historical statues of several closely related attributes in stock market such as volumes, stock market index and daily amplitudes.

Handbook Of Machine Learning - Volume 2: Optimization And Decision Making

Handbook Of Machine Learning - Volume 2: Optimization And Decision Making
Author: Tshilidzi Marwala
Publisher: World Scientific
Total Pages: 321
Release: 2019-11-21
Genre: Computers
ISBN: 981120568X

Building on , this volume on Optimization and Decision Making covers a range of algorithms and their applications. Like the first volume, it provides a starting point for machine learning enthusiasts as a comprehensive guide on classical optimization methods. It also provides an in-depth overview on how artificial intelligence can be used to define, disprove or validate economic modeling and decision making concepts.