Tailored for undergraduate courses in Computer Science & Information Technology/MCA, “Data Mining Introductory and Advanced Topics 2026” is a comprehensive guide that takes students on a journey through the intricacies of data mining algorithms and concepts.
Database Perspective Throughout
Maintaining a database perspective throughout the book, the author provides a focused discussion on algorithms, data structures, data types, and the complexity of algorithms and space. This approach enables students to gain a holistic understanding of data mining, emphasizing its practical applications in real-world scenarios with large database components.
Key Features of Data Mining Introductory and Advanced Topics
– Algorithm Emphasis: The book places a strong emphasis on algorithms, ensuring that students not only understand the concepts but also the underlying processes that drive data mining.
– Real-world Applications: Demonstrating the relevance of data mining concepts, the book explores their application in real-world scenarios, particularly those involving large databases.
Book Details
Edition: 1st
Publisher: Pearson Education India
Publication Date: January 1
Language: English
Dimensions: 20.3 x 25.4 x 4.7 cm
Print Length: 328 pages
Why Choose “Data Mining Introductory and Advanced Topics”?
– **Curriculum Alignment:** Perfectly suited for undergraduate courses, the book aligns with the needs of students in Computer Science and Information Technology/MCA programs.
– **Practical Focus:** By maintaining a database perspective and emphasizing real-world applications, the book ensures that students are well-prepared for applying data mining concepts in professional settings.
– **Comprehensive Approach:** Covering a wide array of data mining topics and algorithms, this book offers a thorough exploration of the subject matter.
Equip yourself with the knowledge and skills essential for navigating the world of data mining. “Data Mining Introductory and Advanced Topics” is your gateway to understanding the intricacies of data mining and applying this knowledge to real-world scenarios.
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Comprehensive Coverage from Basics to Advanced This book covers all important topics of data mining, from basic conceptsto advanced techniques, making it ideal for both beginners and professionals.
Updated for 2026 Syllabus Tailored to meet the needs of 2026 data mining courses, this latest edition aligns with most B.Tech, M.Tech, MCA, and Data Sciencesyllabi.
Concepts Made Simple Written in easy-to-understand language, the book simplifies complex topics like clustering, classification, association rules, web mining, and text mining.
Real-World Examples & Case Studies Includes practical examplesand case studiesto help you understand how data mining is applied in industries like e-commerce, healthcare, and banking.
Practice Questions & Exercises Each chapter ends with MCQs, theoretical questions, and coding-based exercisesto strengthen your preparation for exams or interviews.
Q1. Is this book suitable for beginners in data mining? A:Yes, it starts with the basics and gradually moves to advanced data mining topics, ideal for beginners as well as experienced learners.
Q2. Does the book include practical implementation? A:Yes, it contains real-life case studies and algorithm implementation examplesthat help bridge theory and practical applications.
Q3. Can this book help with GATE or UGC NET preparation? A:Absolutely! It covers key data mining topicsrelevant to GATE CSE, UGC NET CS, and Data Scienceinterviews.
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