Meta-Analytics: Consensus Approaches and System Patterns for Data Analysis

We live in a world in which huge volumes of data are being collected. The machine intelligence community has been very successful in turning this data into information. Taking the power of hybrid architectures as a starting point, analytics approaches can be upgraded. Meta-Analytics supplies 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 behaviour than the use of traditional analytics approaches alone. The book is 'meta' to analytics, and so covers general analytics in sufficient detail for the reader to engage with and understand hybrid or meta- approaches. It allows a relative novice to quickly achieve high-level competency. The title has relevance to machine translation, robotics, biological and social sciences, medical and healthcare informatics, economics, business and finance. The analytics can be applied to predictive algorithms for everyone from police departments to sports analysts Provides comprehensive and systematic coverage of machine learning-based data analysis tasks Enables rapid progress towards competency in data analysis techniques Gives exhaustive and widely applicable patterns for use by data scientists Covers hybrid or 'meta' approaches as well as general analytics Lays out information and practical guidance on data analysis for practitioners working across all sectors

• | Author: Steven Simske
• | Publisher: Morgan Kaufmann
• | Publication Date: Mar 13, 2019
• | Number of Pages: 340 pages
• | Language: English
• | Binding: Paperback
• | ISBN-10: 0128146230
• | ISBN-13: 9780128146231