Artificial Intelligence and Knowledge Processing

Improved Decision-Making and Prediction

• Author(s): Hemachandran K, Raul V. Rodriguez, Umashankar Subramaniam, Valentina Emilia Balas,
• Publisher: CRC Press
• Pages: 386
• ISBN_10: 1000934594
  ISBN_13: 9781000934595
  
• Language: en
• Categories: Computers / Data Science / Machine Learning , Technology & Engineering / Industrial Engineering , Technology & Engineering / Manufacturing , Computers / Artificial Intelligence / General , Computers / Database Administration & Management , Technology & Engineering / Environmental / General , Technology & Engineering / Electrical , Technology & Engineering / Engineering (General) , Technology & Engineering / Automation , Design / Product , Technology & Engineering / Hydraulics , Mathematics / Probability & Statistics / General ,

Description:...

Artificial Intelligence and Knowledge Processing play a vital role in various automation industries and their functioning in converting traditional industries to AI-based factories. This book acts as a guide and blends the basics of Artificial Intelligence in various domains, which include Machine Learning, Deep Learning, Artificial Neural Networks, and Expert Systems, and extends their application in all sectors.

Artificial Intelligence and Knowledge Processing: Improved Decision-Making and Prediction, discusses the designing of new AI algorithms used to convert general applications to AI-based applications. It highlights different Machine Learning and Deep Learning models for various applications used in healthcare and wellness, agriculture, and automobiles. The book offers an overview of the rapidly growing and developing field of AI applications, along with Knowledge of Engineering, and Business Analytics. Real-time case studies are included across several different fields such as Image Processing, Text Mining, Healthcare, Finance, Digital Marketing, and HR Analytics. The book also introduces a statistical background and probabilistic framework to enhance the understanding of continuous distributions. Topics such as Ensemble Models, Deep Learning Models, Artificial Neural Networks, Expert Systems, and Decision-Based Systems round out the offerings of this book.

This multi-contributed book is a valuable source for researchers, academics, technologists, industrialists, practitioners, and all those who wish to explore the applications of AI, Knowledge Processing, Deep Learning, and Machine Learning.