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 usescase 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 LearnDiscover the machine learning, big data, and cloud and cognitive computing technology stackGain insights into machine learning concepts and practices Understand business and enterprise decision-making using machine learningAbsorb machine-learning best practicesWho This Book Is ForManagers tasked with making key decisions who want to learn how and when machine learning and related technologies can help them.

Dr. Patanjali Kashyap hold a degree in Ph.D. (physics) and MCA. Currently he is working as a technology manager in a leading American bank. Professionally he deals with high impact mission critical financial and innovative new generation technology projects on day to day basis. He has worked with the technology giants like Infosys and Cognizant technology solutions. He is an expert of the agile process, machine learning, big data, and cloud computing paradigm. He possesses sound understanding of Microsoft Azure and cognitive computing platforms like Watson and Microsoft cognitive services. He introduces .net technologies as his first love to his friends and colleague. Patanjali has worked on spectrum of .net and associated technologies like Sql server and component based architecture from their inception. Few other technologies on which he loves to work on are SharePoint (content management in general), knowledge management, positive technology, psychological computing and UNIX. Heis vastly experienced in Software development methodologies, Application support and maintenance. 

 He possesses a restless mind which is always looking for innovation and is involved in idea generation for all walks of life including spirituality, positive psychology, brain science and cutting-edge technologies. He is a strong believer in cross/ inter disciplinary study. His view of everything is linked with the other reflects in his work. For example, he has filed a patent on improving and measuring the performance of an individual by using emotional, social, moral and vadantic intelligence. Which presents a unique novel synthesis of management science, physics, information technology and organizational behaviour.

 Patanjali has published several research and white papers on multiple topics. He is involved in a lot of organizational initiatives like building world class teams and dynamic culture across enterprises. He is a go-to person for incorporatingpositivity and enthusiasm in the enterprises. His fresh way of synthesizing Indian Vedic philosophies with the western practical management insight for building flawless organizational dynamics is much appreciated in the corporate circle. He is a real implementer of ancient mythologies at modern work place. Patanjali is also involved in the leadership development and building growth frameworks for the same.

Apart from MCA patanjali holds masters in bioinformatics, physics and computer science (M.Phil.).

 

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, 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.