Data Mining app with syllabus, MCQs & quizzes for learning analytics and KDD.
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About Fundamentals of Data Mining
Fundamentals of Data Mining is an education app developed by StudyZoom.
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Fundamentals of Data Mining has been downloaded 230 times. In the last 30 days, the app was downloaded 25 times.
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Fundamentals of Data Mining is free to download. The APK download size is 24.55 MB. The latest version available is 1.0. The last update was on October 11, 2025.
What are the requirements for Fundamentals of Data Mining?
The app has a content rating of Everyone. The app has been available on Google Play October 2025.
Description
π Fundamentals of Data Mining (2025–2026 Edition)
π Fundamentals of Data Mining (2025–2026 Edition) is a comprehensive syllabus-based textbook designed for BSCS, BSIT, and Software Engineering students, as well as professionals and self-learners who want to explore the science of extracting knowledge from data.
This edition provides a balanced blend of theory, techniques, and practical applications, supported by MCQs, and quizzes for effective learning. Students will develop essential data mining skills, from data preprocessing and classification to clustering, association, and advanced mining methods.
The book bridges the gap between statistical learning and real-world analytics, making it ideal for academic courses, research projects, and industry applications involving big data, AI, and business intelligence.
π Chapters & Topics
πΉ Chapter 1: Introduction to Data Mining
-What is Data Mining? -Knowledge Discovery in Databases (KDD) Process -Applications of Data Mining in Business, Science, and Social Media -Challenges and Issues in Data Mining
πΉ Chapter 2: Data Preparation and Preprocessing
-Data Cleaning and Integration -Data Reduction Techniques (Dimensionality Reduction, Feature Selection) -Data Transformation and Normalization -Handling Missing and Noisy Data
πΉ Chapter 3: Learning from Data (Supervised & Unsupervised)
-Statistical Methods in Data Mining -Decision Trees and Decision Rules -Artificial Neural Networks (ANN) -Ensemble Learning (Bagging, Boosting, Random Forest)
πΉ Chapter 4: Clustering and Association Analysis
-Cluster Analysis (K-Means, Hierarchical, DBSCAN) -Evaluation of Clustering Results -Association Rule Mining (Apriori, FP-Growth) -Applications of Clustering and Association
πΉ Chapter 5: Advanced Data Mining Techniques -Web Mining and Text Mining -Genetic Algorithms in Data Mining -Fuzzy Sets and Fuzzy Logic for Decision Making -Visualization Methods in Data Mining
πΉ Chapter 6: Data Mining Tools and Applications -Overview of Popular Tools: Weka, CBA, Yale (RapidMiner) -Industry Applications (Healthcare, Finance, E-Commerce, Cybersecurity) -Big Data and Data Mining (Hadoop, Spark Basics) -Ethical and Privacy Issues in Data Mining
π Why Choose This Book/App?
β Complete syllabus coverage for academic and professional learning β Includes MCQs, quizzes, and practical case studies β Covers both traditional and modern data mining algorithms β Ideal for students, data analysts, and AI/ML enthusiasts β Strengthens understanding of real-world data analytics and big data tools
βThis app is inspired by the authors: Jiawei Han, Micheline Kamber, Ian H. Witten, Eibe Frank, Pang-Ning Tan
π₯ Download Now!
Master the art and science of knowledge discovery with Fundamentals of Data Mining (2025–2026 Edition) — your complete guide to modern data mining techniques and applications.
Recent changes: π Initial Launch of Fundamentals of Data Mining
β¨ What’s Inside: β Complete syllabus book covering core data mining concepts & techniques β MCQs and quizzes for concept mastery, practice, & exam preparation
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