Machine Learning and Its Application: A Quick Guide for Beginners aims to cover most of the core topics required for study in machine learning curricula included in university and college courses. The textbook introduces readers to central concepts in machine learning and artificial intelligence, which include the types of machine learning algorithms and the statistical knowledge required for devising relevant computer algorithms. The book also covers advanced topics such as deep learning and feature engineering.
Key features:
- 8 organized chapters on core concepts of machine learning for learners
- Accessible text for beginners unfamiliar with complex mathematical concepts
- Introductory topics are included, including supervised learning, unsupervised learning, reinforcement learning, and predictive statistics
- Advanced topics such as deep learning and feature engineering provide additional information
- Introduces readers to python programming with examples of code for understanding and practice
- Includes a summary of the text and a dedicated section for references
Machine Learning and Its Application: A Quick Guide for Beginners is an essential book for students and learners who want to understand the basics of machine learning and equip themselves with the knowledge to write algorithms for intelligent data processing applications.
About the Author:
Dr. Indranath Chatterjee is a Professor in the Department of Computer Engineering at Tongmyong University, Busan, South Korea. He received his Ph. D. in Computational Neuroscience from the Department of Computer Science, University of Delhi, India. His research areas include Computational Neuroscience, Schizophrenia, Medical Imaging, fMRI, and Machine learning. He has authored and edited 8 books on Computer Science and Neuroscience published by renowned international publishers. To date, he has published numerous research papers in international journals and conferences. He is a recipient of various global awards on neuroscience. He is currently serving as a Chief Section Editor of a few renowned international journals and serving as a member of the Advisory board and Editorial board of various international journals and Open-Science organizations worldwide. He is presently working on several projects of government & non-government organizations as PI/co-PI, related to medical imaging and machine learning for a broader societal impact, in collaboration with several universities globally. He is an active professional member of the Association of Computing Machinery (ACM, USA), Organization of Human Brain Mapping (OHBM, USA), Federations of European Neuroscience Society (FENS, Belgium), Association for Clinical Neurology and Mental Health (ACNM, India), and International Neuroinformatics Coordinating Facility (INCF, Sweden).
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