Meta-Analytics

Consensus Approaches and System Patterns for Data Analysis

Steven Simske (HP Fellow and Director, HP Labs, HP Inc, CO, USA)

$116.95

Paperback

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English

Morgan Kaufmann Publishers In
13 March 2019

Data capture & analysis; Machine learning

Meta-Analytics: Consensus Approaches and System Patterns for Data Analysis presents an exhaustive set of patterns for data science to use on any machine learning based data analysis task. The book virtually ensures that at least one pattern will lead to better overall system behavior than the use of traditional analytics approaches. The book is ‘meta’ to analytics, covering general analytics in sufficient detail for readers to engage with, and understand, hybrid or meta- approaches. The book has relevance to machine translation, robotics, biological and social sciences, medical and healthcare informatics, economics, business and finance.

Inn addition, the analytics within can be applied to predictive algorithms for everyone from police departments to sports analysts.

By: Steven Simske (HP Fellow and Director HP Labs HP Inc CO USA)
Imprint: Morgan Kaufmann Publishers In
Country of Publication: United States
Dimensions: Height: 234mm, Width: 191mm,
Weight: 700g
ISBN: 9780128146231
ISBN 10: 0128146230
Pages: 340
Publication Date: 13 March 2019
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

Steven J Simske is HP Fellow and Director at Hewlett Packard Labs, and has worked in machine intelligence and analytics for the past 25 years, with domains extending from medical image analytics to text summarization. He has performed research relevant to meta analytics for over 20 years at HP Labs, and in collaboration with major universities in the US and Brazil.