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Meta-Analytics

Steven Simske
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      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.
      Format: CONTRIBUTORS: Steven Simske EAN: 9780128146231 COUNTRY: United States PAGES: WEIGHT: 700 g HEIGHT: 235 cm
      PUBLISHED BY: Elsevier Science & Technology DATE PUBLISHED: 2019-03-13 CITY: GENRE: COMPUTERS / Artificial Intelligence / General, COMPUTERS / Data Science / General WIDTH: 191 cm SPINE:

      Book Themes:

      Data capture and analysis, Machine learning

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      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.
      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.
      Format: CONTRIBUTORS: Steven Simske EAN: 9780128146231 COUNTRY: United States PAGES: WEIGHT: 700 g HEIGHT: 235 cm
      PUBLISHED BY: Elsevier Science & Technology DATE PUBLISHED: 2019-03-13 CITY: GENRE: COMPUTERS / Artificial Intelligence / General, COMPUTERS / Data Science / General WIDTH: 191 cm SPINE:

      Book Themes:

      Data capture and analysis, Machine learning

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      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.

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