Description

Book Synopsis
This book describes the deep learning models and ensemble approaches applied to decision-making problems. The authors have addressed the concepts of deep learning, convolutional neural networks, recurrent neural networks, and ensemble learning in a practical sense providing complete code and implementation for several real-world examples. The authors of this book teach the concepts of machine learning for undergraduate and graduate-level classes and have worked with Fortune 500 clients to formulate data analytics strategies and operationalise these strategies. The book will benefit information professionals, programmers, consultants, professors, students, and industry experts who seek a variety of real-world illustrations with an implementation based on machine learning algorithms.

Table of Contents
Preface; Acknowledgements; Introduction; Deep Learning; Convolutional Neural Networks; Recurrent Neural Networks; Ensemble Learning; Implementing DL and Ensemble Learning Models: Real World Use Cases; Appendix; Suggested Reading; About the Authors; Index.

Advanced Decision Sciences Based on Deep Learning

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    A Hardback by Surekha Paneerselvam

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      Book details

      Publisher Nova Science Publishers Inc
      Published 1 December 2021
      ISBN-13 9781685070618
      978-1685070618
      ISBN-10 1685070612

      Description

      Book Synopsis
      This book describes the deep learning models and ensemble approaches applied to decision-making problems. The authors have addressed the concepts of deep learning, convolutional neural networks, recurrent neural networks, and ensemble learning in a practical sense providing complete code and implementation for several real-world examples. The authors of this book teach the concepts of machine learning for undergraduate and graduate-level classes and have worked with Fortune 500 clients to formulate data analytics strategies and operationalise these strategies. The book will benefit information professionals, programmers, consultants, professors, students, and industry experts who seek a variety of real-world illustrations with an implementation based on machine learning algorithms.

      Table of Contents
      Preface; Acknowledgements; Introduction; Deep Learning; Convolutional Neural Networks; Recurrent Neural Networks; Ensemble Learning; Implementing DL and Ensemble Learning Models: Real World Use Cases; Appendix; Suggested Reading; About the Authors; Index.

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