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{ "item_title" : "Machine Learning for Intelligent Decision Science", "item_author" : [" Jitendra Kumar Rout", "Minakhi Rout", "Himansu Das "], "item_description" : "The book discusses machine learning-based decision-making models, and presents intelligent, hybrid and adaptive methods and tools for solving complex learning and decision-making problems under conditions of uncertainty. Featuring contributions from data scientists, practitioners and educators, the book covers a range of topics relating to intelligent systems for decision science, and examines recent innovations, trends, and practical challenges in the field. The book is a valuable resource for academics, students, researchers and professionals wanting to gain insights into decision-making.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/9/81/153/688/9811536880_b.jpg", "price_data" : { "retail_price" : "179.99", "online_price" : "179.99", "our_price" : "179.99", "club_price" : "179.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Machine Learning for Intelligent Decision Science|Jitendra Kumar Rout

Machine Learning for Intelligent Decision Science

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Overview

The book discusses machine learning-based decision-making models, and presents intelligent, hybrid and adaptive methods and tools for solving complex learning and decision-making problems under conditions of uncertainty. Featuring contributions from data scientists, practitioners and educators, the book covers a range of topics relating to intelligent systems for decision science, and examines recent innovations, trends, and practical challenges in the field. The book is a valuable resource for academics, students, researchers and professionals wanting to gain insights into decision-making.


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Details

  • ISBN-13: 9789811536885
  • ISBN-10: 9811536880
  • Publisher: Springer
  • Publish Date: April 2020
  • Dimensions: 9.21 x 6.14 x 0.56 inches
  • Shipping Weight: 1.08 pounds
  • Page Count: 209

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