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2014 8th Asia Modelling Symposium Ams 2014

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2014 8th Asia Modelling Symposium Ams 2014

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Author :
language : en
Publisher:
Release Date : 2014

2014 8th Asia Modelling Symposium Ams 2014 written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Computer simulation categories.

2014 8th Asia Modelling Symposium Ams

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Author : IEEE Staff
language : en
Publisher:
Release Date : 2014-09-23

2014 8th Asia Modelling Symposium Ams written by IEEE Staff and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-09-23 with categories.

Analytical and mathematical modelling and simulation of a variety of application areas within computing science and technology and systems engineering emphasizing the role of intelligent system and hybrid intelligent systems and soft computing

2014 8th Asia Modelling Symposium Ams 2014

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Author :
language : en
Publisher:
Release Date : 2014

2014 8th Asia Modelling Symposium Ams 2014 written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with categories.

Asia Modelling Symposium 2014

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Author : David Al-Dabass
language : en
Publisher:
Release Date : 2014

Asia Modelling Symposium 2014 written by David Al-Dabass and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Computer simulation categories.

Ams 2015

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Author : Asia International Conference on Mathematical Modelling and Computer Simulation
language : en
Publisher:
Release Date : 2015

Ams 2015 written by Asia International Conference on Mathematical Modelling and Computer Simulation and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Computer simulation categories.

Ams 2015

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Author : David Al-Dabass
language : en
Publisher:
Release Date : 2015

Ams 2015 written by David Al-Dabass and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.

Advances In Machine Learning And Data Science

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Author : Damodar Reddy Edla
language : en
Publisher: Springer
Release Date : 2018-05-16

Advances In Machine Learning And Data Science written by Damodar Reddy Edla and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-16 with Technology & Engineering categories.

The Volume of “Advances in Machine Learning and Data Science - Recent Achievements and Research Directives” constitutes the proceedings of First International Conference on Latest Advances in Machine Learning and Data Science (LAMDA 2017). The 37 regular papers presented in this volume were carefully reviewed and selected from 123 submissions. These days we find many computer programs that exhibit various useful learning methods and commercial applications. Goal of machine learning is to develop computer programs that can learn from experience. Machine learning involves knowledge from various disciplines like, statistics, information theory, artificial intelligence, computational complexity, cognitive science and biology. For problems like handwriting recognition, algorithms that are based on machine learning out perform all other approaches. Both machine learning and data science are interrelated. Data science is an umbrella term to be used for techniques that clean data and extract useful information from data. In field of data science, machine learning algorithms are used frequently to identify valuable knowledge from commercial databases containing records of different industries, financial transactions, medical records, etc. The main objective of this book is to provide an overview on latest advancements in the field of machine learning and data science, with solutions to problems in field of image, video, data and graph processing, pattern recognition, data structuring, data clustering, pattern mining, association rule based approaches, feature extraction techniques, neural networks, bio inspired learning and various machine learning algorithms.