Machine Learning is one of the fastest-growing fields in Computer Science and Artificial Intelligence, and today it is an essential subject for undergraduate students in programs like BCA and B.Sc. Computer Science. However, most books available in the market are filled with complex mathematics and technical jargon, making it difficult for beginners to truly understand the concepts.
Machine Learning Made Simple is specially designed for students and first-time learners who want to build a strong foundation without getting lost in complicated theories. Instead of focusing on heavy mathematics, this book emphasizes clarity, logic, and real understanding.
Inside this book, you will discover:
Clear and simple explanations of core Machine Learning concepts
Step-by-step breakdown of important algorithms
Easy-to-understand diagrams and illustrations
Real-life examples that connect theory to practical use
Fundamental learning approaches including supervised and unsupervised learning
Whether you are a student or a beginner exploring Machine Learning for the first time, this book will help you move from confusion to confidence.
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Dr. S. Jeya Selvakumari, M. Selvi
Dr. S. Jeya Selvakumari is an Assistant Professor in the Department of Computer Science, Kamaraj College (Autonomous), Thoothukudi, with over 18 years of teaching experience. She holds MCA, B.Ed., M.Phil., and Ph.D. degrees and has qualified SET and NET examinations. Her areas of interest include Artificial Intelligence, Machine Learning, Deep Learning Data Science. She is committed to simplifying complex concepts and making learning accessible to undergraduate students. Her work reflects a strong dedication to academic excellence and student-centered learning.
Mrs. M. Selvi is a dedicated academician serving as a Guest Lecturer in the Department of Computer Science with 8 years of teaching experience. She holds MCA and M.Phil. degrees and has qualified the SET and NET examinations, reflecting strong subject knowledge and professional competence. She specializes in Data Structures and Algorithms and is proficient in multiple programming languages. Her research interests include Machine Learning and Image Processing. She adopts concept-oriented teaching methods and actively contributes to students’ academic and personal growth.
