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DataMining-Books

"Data Mining: Concepts and Techniques" authored by Jiawei Han, Micheline Kamber, and Jian Pei:


Data Mining: Concepts and Techniques

This repository contains resources and supplementary materials related to the book "Data Mining: Concepts and Techniques" authored by Jiawei Han, Micheline Kamber, and Jian Pei.

About the Book

"Data Mining: Concepts and Techniques" is a comprehensive textbook that covers fundamental concepts, methodologies, algorithms, and applications in the field of data mining. Authored by experts in the field, the book serves as an essential resource for students, researchers, and practitioners interested in exploring the theory and practice of data mining.

Contents

  • Datasets: Sample datasets used in the book for illustrating various data mining techniques and algorithms.
  • Code Examples: Implementation of algorithms and techniques discussed in the book, provided in various programming languages such as Python, R, and Java.
  • Slides: Presentation slides corresponding to chapters or topics covered in the book, suitable for teaching or self-study purposes.
  • Exercises and Solutions: Exercise questions and solutions for readers to practice and reinforce their understanding of the concepts presented in the book.

How to Use

  1. Datasets: Download the datasets for experimentation and analysis.
  2. Code Examples: Explore the provided code examples to understand the implementation of data mining algorithms.
  3. Slides: Review the presentation slides for each chapter to gain insights into the theoretical concepts discussed in the book.
  4. Exercises and Solutions: Test your knowledge and understanding by attempting the exercise questions and referring to the solutions provided.

Contributing

Contributions to enhance and expand the resources in this repository are welcome! If you have additional datasets, code examples, slides, or exercise solutions related to the book, feel free to submit a pull request with your contributions.

Please ensure that your contributions adhere to the existing structure and follow best practices for documentation and code formatting.

License

The materials in this repository are provided under the MIT License, unless otherwise stated.

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