Machine Learning for Decision Makers: Cognitive Computing Fundamentals for Better Decision Making

Machine Learning for Decision Makers: Cognitive Computing Fundamentals for Better Decision Making Front Cover
Machine Learning for Decision Makers: Cognitive Computing Fundamentals for Better Decision Making
By 作者: Patanjali Kashyap
Pages 页数: 355 pages
Edition 版本: 1st ed.
Language 语言: English
Publisher Finelybook 出版社: Apress
Publication Date 出版日期: 2018-02-02
ISBN-10 书号:1484229878
ISBN-13 书号:9781484229873

The Book Description robot was collected from Amazon and arranged by Finelybook

Take a deep dive into the concepts of machine learning as they apply to contemporary business and management. You will learn how machine learning techniques are used to solve fundamental and complex problems in society and industry. Machine Learning for Decision Makers serves as an excellent resource for establishing the relationship of machine learning with IoT, big data, and cognitive and cloud computing to give you an overview of how these modern areas of computing relate to each other.
This book introduces a collection of the most important concepts of machine learning and sets them in context with other vital technologies that decision makers need to know about. These concepts span the process from envisioning the problem to applying machine-learning techniques to your particular situation. This discussion also provides an insight to help deploy the results to improve decision-making.
The book uses case studies and jargon busting to help you grasp the theory of machine learning quickly. You'll soon gain the big picture of machine learning and how it fits with other cutting-edge IT services. This knowledge will give you confidence in your decisions for the future of your business.
What You Will Learn
Discover the machine learning, big data, and cloud and cognitive computing technology stack
Gain insights into machine learning concepts and practices
Understand business and enterprise decision-making using machine learning
Absorb machine-learning best practices
Who This Book Is For
Managers tasked with making key decisions who want to learn how and when machine learning and related technologies can help them.

Contents


Chapter 1: Let’s Integrate with Machine Learning
Chapter 2: The Practical Concepts of Machine Learning
Chapter 3: Machine Learning Algorithms and Their Relationship with Modern Technologies
Chapter 4: Technology Stack for Machine Learning and Associated Technologies
Chapter 5: Industrial Applications of Machine Learning
Chapter 6: I Am the Future: Machine Learning in Action
Chapter 7: Innovation, KPIs, Best Practices, and More for Machine Learning
Chapter 8: Do Not Forget Me: The Human Side of Machine Learning
Chapter 9: Let’s Wrap Up: The Final Destination
Appendix A: How to Architect and Build a Machine Learning Solution
Appendix B: A Holistic Machine Learning and Agile-Based Software Methodology
Appendix C: Data Processing Technologies

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