Machine learning for business analytics : real-time data analysis for decision making /
Machine learning for business analytics : real-time data analysis for decision making /
edited by Hemachandran K., Sayantan Khanra, Raul V. Rodriguez, Juan R. Jaramillo
- New York, NY : Routledge, 2023
- xiii, 173 pages : illustrations ; 26 cm.
Tables.
Include index.
Contents:
Chapter 1: Introduction to machine learning;
Chapter 2: Role of machine learning in promoting sustainability;
Chapter 3: Addressing the utilization of popular regression models in business application;
Chapter 4: Chatbots: their uses and impact in the hospitality sector;
Chapter 5: Traversing through the use of robotics in the medical industry: outlining emerging trends and perspectives for future growth;
Chapter 6: Integration of AI in insurance and healthcare;
Chapter 7: Artificial intelligence in agriculture: a review;
Chapter 8:Machine learning and artificial intelligence-based tools in digital marketing: and integrated approach;
Chapter 9: Application of artificial intelligence in market knowledge and B2B marketing co-creation;
Chapter 10: A systematic literature review of the impact of artificial intelligence on customer experience;
Chapter 11: The impact of artificial intelligence on customer experience and the purchasing process;
Chapter 12: Application of artificial intelligence in banking: a review;
Chapter 13: Digital ethics: toward a socially prefereble development of AI systems.
"MACHINE LEARNING FOR BUSINESS ANALYTICS. Machine learning is an integral tool in business analyst's arsenal because the rate at which data is being generated from different sources is increasing and working on complex unstructured data is becoming inevitable. Date collection, data cleaning, and data mining are rapidly becoming more difficult to analyze than just importing information from a primary or secondary source. The machine learning model plays crucial rule in predicting the future performance and results of a company. In real-time, date collection and data wrangling are the important steps in deploying the models. Analytics is a tool for visualizing and steering data and statistics. Business analysts can work with different datasets-choosing an appropriate machine learning model results in accurate analyzing, forecasting the future and making informed decisions. The global machine learning market was valued at $1.58 billion in 2017 and is expected to reach $20.83 billion in 2024-growing at a CAGR of 44.06 % between 2017 and 2024. The authors have compiled important knowledge on machine learning real-time applications in business analytics. This book enables readers to get broad knowledge in the field of machine learning models and to carry out their future work. The future trends machine learning for business analytics are explained with real case studies. Essentially, this book act as a guide to all business analysts. The authors blend the basics of data analytics and machine learning and extend its application to business analytics. This book act as a superb introduction covers the application to business and implications of machine learning. The authors provide the first-hand experience with machine learning and data analytics. This book is valuable source for practitioners, industrialists, technologists, and researchers." --Provided by the publisher
9781032072777 [paperback]. Mindmovers : ₱7,112.40
Machine learning.
Data mining.
001.31 / M18 2023
Tables.
Include index.
Contents:
Chapter 1: Introduction to machine learning;
Chapter 2: Role of machine learning in promoting sustainability;
Chapter 3: Addressing the utilization of popular regression models in business application;
Chapter 4: Chatbots: their uses and impact in the hospitality sector;
Chapter 5: Traversing through the use of robotics in the medical industry: outlining emerging trends and perspectives for future growth;
Chapter 6: Integration of AI in insurance and healthcare;
Chapter 7: Artificial intelligence in agriculture: a review;
Chapter 8:Machine learning and artificial intelligence-based tools in digital marketing: and integrated approach;
Chapter 9: Application of artificial intelligence in market knowledge and B2B marketing co-creation;
Chapter 10: A systematic literature review of the impact of artificial intelligence on customer experience;
Chapter 11: The impact of artificial intelligence on customer experience and the purchasing process;
Chapter 12: Application of artificial intelligence in banking: a review;
Chapter 13: Digital ethics: toward a socially prefereble development of AI systems.
"MACHINE LEARNING FOR BUSINESS ANALYTICS. Machine learning is an integral tool in business analyst's arsenal because the rate at which data is being generated from different sources is increasing and working on complex unstructured data is becoming inevitable. Date collection, data cleaning, and data mining are rapidly becoming more difficult to analyze than just importing information from a primary or secondary source. The machine learning model plays crucial rule in predicting the future performance and results of a company. In real-time, date collection and data wrangling are the important steps in deploying the models. Analytics is a tool for visualizing and steering data and statistics. Business analysts can work with different datasets-choosing an appropriate machine learning model results in accurate analyzing, forecasting the future and making informed decisions. The global machine learning market was valued at $1.58 billion in 2017 and is expected to reach $20.83 billion in 2024-growing at a CAGR of 44.06 % between 2017 and 2024. The authors have compiled important knowledge on machine learning real-time applications in business analytics. This book enables readers to get broad knowledge in the field of machine learning models and to carry out their future work. The future trends machine learning for business analytics are explained with real case studies. Essentially, this book act as a guide to all business analysts. The authors blend the basics of data analytics and machine learning and extend its application to business analytics. This book act as a superb introduction covers the application to business and implications of machine learning. The authors provide the first-hand experience with machine learning and data analytics. This book is valuable source for practitioners, industrialists, technologists, and researchers." --Provided by the publisher
9781032072777 [paperback]. Mindmovers : ₱7,112.40
Machine learning.
Data mining.
001.31 / M18 2023