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Machine learning for decision makers : cognitive computing fundamentals for better decision making /
Take a deep dive into the essential elements of machine learning. You will learn how machine learning techniques are used to solve fundamental and complex problems in society and industry. Machine Learning for Managers serves as an excellent resource for establishing the relationship of machine lear...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
New York, NY :
Apress,
[2017]
|
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Kashyap, Patanjali, |e author. | |
| 245 | 1 | 0 | |a Machine learning for decision makers : |b cognitive computing fundamentals for better decision making / |c Patanjali Kashyap. |
| 264 | 1 | |a New York, NY : |b Apress, |c [2017] | |
| 300 | |a 1 online resource | ||
| 336 | |a text |b txt |2 rdacontent | ||
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| 347 | |a text file | ||
| 588 | 0 | |a Vendor-supplied metadata. | |
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Chapter 1: Introduction -- Chapter 2: Fundamentals of Machine Learning and its technical ecosystem -- Chapter 3: Methods and techniques of Machine Learning -- Chapter 4: Machine Learning and its relationship with cloud, IOT, big data and cognitive computing in business perspective -- Chapter 5: Business challenges and applications of Machine Learning big data, IOT, cloud and cognitive computing in different fields and domains -- Chapter 6: Technology offered by different vendors for Machine Learning -- Chapter 7: Security and Machine Learning -- Visual and text summery of the chapter -- Chapter 8: Matrices, KPI's and more. For Machine Learning ecosystem -- Chapter 9: Best practices and pattern for Machine Learning -- Chapter 10: Recent advancement and future directions of Machine Learning -- Chapter 11: Conclusion. | |
| 520 | |a Take a deep dive into the essential elements of machine learning. You will learn how machine learning techniques are used to solve fundamental and complex problems in society and industry. Machine Learning for Managers serves as an excellent resource for establishing the relationship of machine learning with IoT, big data, and cognitive and cloud computing. This book introduces a collection of the most important fundamental concepts of machine learning and its associated fields. These concepts span the process from envisioning the problem to applying machine-learning techniques to the enterprise. This discussion also provides an insight to help deploy the results to improve decision-making. The book uses practical examples and use cases that will help you grasp the concepts of machine learning quickly. It concludes with a section on how using this technology will become a game-changer in the years to come. You will: 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 See the latest research, trends, and security frameworks in the machine learning space Use machine-learning best practices. | ||
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Decision making. | |
| 650 | 0 | |a Machine learning. | |
| 650 | 2 | |a Decision Making | |
| 650 | 2 | |a Machine Learning | |
| 650 | 1 | 4 | |a Computer Science. |
| 650 | 2 | 4 | |a Computing Methodologies. |
| 650 | 2 | 4 | |a Software Engineering. |
| 650 | 2 | 4 | |a Algorithm Analysis and Problem Complexity. |
| 650 | 6 | |a Prise de décision. | |
| 650 | 6 | |a Apprentissage automatique. | |
| 650 | 7 | |a decision making. |2 aat | |
| 650 | 7 | |a Software Engineering. |2 bicssc | |
| 650 | 7 | |a Algorithms & data structures. |2 bicssc | |
| 650 | 7 | |a Artificial intelligence. |2 bicssc | |
| 650 | 7 | |a MATHEMATICS |x Applied. |2 bisacsh | |
| 650 | 7 | |a MATHEMATICS |x Probability & Statistics |x General. |2 bisacsh | |
| 650 | 7 | |a Decision making |2 fast | |
| 650 | 7 | |a Machine learning |2 fast | |
| 776 | 0 | 8 | |i Printed edition: |z 9781484229873 |
| 856 | 4 | 0 | |u https://learning.oreilly.com/library/view/~/9781484229880/?ar |z Texto completo (Requiere registro previo con correo institucional) |
| 880 | 0 | |6 505-00/$1 |a Chapter 1: 鮴troduction -- Chapter 2: 浮ndamentals of Machine Learning and its technical ecosystem -- Chapter 3: Methods and techniques of Machine Learning -- Chapter 4: Machine Learning and its relationship with cloud, IOT, big data and cognitive computing in business perspective -- Chapter 5: Business challenges and applications of Machine Learning big data, IOT, cloud and cognitive computing in different fields and domains -- Chapter 6: Technology offered by different vendors for Machine Learning -- Chapter 7: Security and Machine Learning -- Visual and text summery of the chapter -- Chapter 8: Matrices, KPIs and more. For Machine Learning ecosystem -- Chapter 9: Best practices and pattern for Machine Learning -- Chapter 10: Recent advancement and future directions of Machine Learning -- Chapter 11: Conclusion. | |
| 880 | |6 520-00/Hani |a Take a deep dive into the essential elements of machine learning. You will learn how machine learning techniques are used to solve fundamental and complex problems in society and industry.chine Learning for Managers㥲ves as an excellent resource for establishing the relationship of machine learning with IoT, big data, and cognitive and cloud computing.Ԩis book introduces a collection of the most important fundamental concepts of machine learning and its associated fields. These concepts span the process from envisioning the problem to applying machine-learning techniques to the enterprise. This discussion also provides an insight to help deploy the results to improve decision-making. The book uses practical examples and use cases that will help you grasp the concepts of machine learning quickly. It concludes with a section on how using this technology will become a game-changer in the years to come. You will: Discover the machine learning, big data, and cloud and cognitive computing technology stack Gain insights into machine learning concepts and practicesծderstand business and enterprise decision-making using machine learning See the latest research, trends, and security frameworks in the machine learning space Use machine-learning best practices. | ||
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