Artificial Intelligence and Machine Learning for Business

Artificial intelligence and machine learning are integral parts of every business today, in areas ranging from finance, strategic decision-making , HR operations, and sales and marketing to manufacturing and more. However, there is a general perception that artificial intelligence and machine learning are only used in the IT sector by large companies with extensive research teams. This new book, Artificial Intelligence and Machine Learning for Business, demonstrates how artificial intelligence and machine learning can be used in every aspect of business and as a foundation for complex decision-making. This book offers an overview of artificial intelligence (AI) techniques that are used in business. Covering such topics as use of AI in employee training, in stock market prediction, in traffic detection, in opinion mining, in fraud detection, for retail purchase predictions, in online customer support interactions, and more. The book proves the diverse ways AI can be used in many facets of a business. The use of AI is also explored in fields such as garbage systems, agriculture, precious metals, banking, HR hiring, and so on. It provides an overview of the most popular and frequently used methods, procedures, and models to control business activity. This book explains in a simplified manner AI standards and concepts for management students and executives. Overall, the book emphasizes the potential business prospects of AI, machine learning, and the derived benefits of using these innovative technologies. Key features: Describes the various capacities where AI is emerging as a game-changer for industries and businesses Addresses key issues, trends, and future perspectives of using AI and ML in business Provides insights into how AI is revolutionizing decision-making, management, early alerts, visual inspection, etc. Leverages AI for managerial tasks as one of the most promising areas of development and data analysis This volume will be of benefit to researchers, academicians, business and industry professionals, and well as faculty and students in the fields of business management, business analytics, social sciences, and data informatics.