Machine Learning for Business Analytics

Machine Learning for Business Analytics: Real-Time Data Analysis for Decision-Making by Sayantan Khanra

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Machine learning is increasingly recognized for playing a crucial role in predicting business performances for frms across the world. On the one hand, data collection and data wrangling are the important steps in training machine learning models. On the other hand, business analytics includes various tools for visualizing and steering data to deliver insights in management decisions. An expert business analyst may work with different data sets, choose appropriate machine learning models, and deliver valuable insights to improve business performances.

A report published by Market Research Future predicts that the global machine learning market will grow at over 44% compound annual growth rate till 2024 to reach $20.83 billion, up from $1.58 billion in 2017. Needless to say, the adoption of machine learning in business enterprises would create enormous opportunities for students and professionals with the required skill set. This book aims to help machine learning enthusiasts better prepare for the opportunity.

Overall, this book captures applications of machine learning in different contexts, such as agriculture, B2B marketing, banking, customer experience, digital marketing, healthcare, hospitality, insurance, and sustainable development. The book is comprised of 13 chapters.

We take this opportunity to express our sincere gratitude to the authors of the 13 chapters in this book. The authors include academicians from renowned institutions and industry experts with relevant experience. We believe that this book will be of signifcant value to different interest groups that wish to explore the applications of machine learning. Finally, we wholeheartedly thank our editorial team for extending persistent support to publish this book.



  • CC BY-NC-SA 3.0 PH
  • The author's reference is not required

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