Fundamentals of Machine Learning for Predictive Data Analytics

Algorithms, Worked Examples, and Case Studies

Author: John D. Kelleher

Publisher: MIT Press


Category: Computers

Page: 624

View: 774

A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.

Analytics in Healthcare

A Practical Introduction

Author: Christo El Morr

Publisher: Springer


Category: Medical

Page: 105

View: 459

This book offers a practical introduction to healthcare analytics that does not require a background in data science or statistics. It presents the basics of data, analytics and tools and includes multiple examples of their applications in the field. The book also identifies practical challenges that fuel the need for analytics in healthcare as well as the solutions to address these problems. In the healthcare field, professionals have access to vast amount of data in the form of staff records, electronic patient record, clinical findings, diagnosis, prescription drug, medical imaging procedure, mobile health, resources available, etc. Managing the data and analyzing it to properly understand it and use it to make well-informed decisions can be a challenge for managers and health care professionals. A new generation of applications, sometimes referred to as end-user analytics or self-serve analytics, are specifically designed for non-technical users such as managers and business professionals. The ability to use these increasingly accessible tools with the abundant data requires a basic understanding of the core concepts of data, analytics, and interpretation of outcomes. This book is a resource for such individuals to demystify and learn the basics of data management and analytics for healthcare, while also looking towards future directions in the field.

Machine Learning and Data Mining in Pattern Recognition

13th International Conference, MLDM 2017, New York, NY, USA, July 15-20, 2017, Proceedings

Author: Petra Perner

Publisher: Springer


Category: Computers

Page: 452

View: 348

This book constitutes the refereed proceedings of the 13th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2017, held in New York, NY, USA in July/August 2017.The 31 full papers presented in this book were carefully reviewed and selected from 150 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.

The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018)

Author: Aboul Ella Hassanien

Publisher: Springer


Category: Computers

Page: 717

View: 339

This book presents the refereed proceedings of the third International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2018, held in Cairo, Egypt, on February 22–24, 2018, and organized by the Scientific Research Group in Egypt (SRGE). The papers cover current research in machine learning, big data, Internet of Things, biomedical engineering, fuzzy logic, security, and intelligence swarms and optimization.

Springer Handbook of Automation

Author: Shimon Y. Nof

Publisher: Springer Science & Business Media


Category: Technology & Engineering

Page: 1812

View: 902

This handbook incorporates new developments in automation. It also presents a widespread and well-structured conglomeration of new emerging application areas, such as medical systems and health, transportation, security and maintenance, service, construction and retail as well as production or logistics. The handbook is not only an ideal resource for automation experts but also for people new to this expanding field.

Issues in Biological and Life Sciences Research: 2011 Edition


Publisher: ScholarlyEditions


Category: Science

Page: 5106

View: 792

Issues in Biological and Life Sciences Research: 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Biological and Life Sciences Research. The editors have built Issues in Biological and Life Sciences Research: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Biological and Life Sciences Research in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Biological and Life Sciences Research: 2011 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at