---
product_id: 742497373
title: "Data Mining: Practical Machine Learning Tools and Techniques"
price: "119223 ₸"
currency: KZT
in_stock: true
reviews_count: 5
url: https://kazakhstan.desertcart.com/products/742497373-data-mining-practical-machine-learning-tools-and-techniques
store_origin: KZ
region: Kazakhstan
---

# Data Mining: Practical Machine Learning Tools and Techniques

**Price:** 119223 ₸
**Availability:** ✅ In Stock

## Quick Answers

- **What is this?** Data Mining: Practical Machine Learning Tools and Techniques
- **How much does it cost?** 119223 ₸ with free shipping
- **Is it available?** Yes, in stock and ready to ship
- **Where can I buy it?** [kazakhstan.desertcart.com](https://kazakhstan.desertcart.com/products/742497373-data-mining-practical-machine-learning-tools-and-techniques)

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## Description

Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches. Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research. Please visit the book companion website at http://www.cs.waikato.ac.nz/ml/weka/book.html It contains Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.

Review: Four Stars - The front page is featuring wrongly as geophysics.
Review: Continues to lead introductions to data mining - I've read and reviewed the 1st, 2nd and now the 4th edition. The authors are genuine experts, at the front of their fields, and by adding new contributors have been able to both update existing topics as well as add authoritative treatments of new ones. I recommend this text to anyone seeking a serious introduction to data mining. The emphasis is practical rather than theoretical, but there are pointers to the theoretical literature for those wanting them. The practical emphasis serves those wanting such, and provides motivation and context for the approach. For those with the necessary mathematical, statistical and computing background there are certainly a plethora of more advanced treatments, but Witten et.al. may well be the best available introduction to the subject for almost everyone.

## Technical Specifications

| Specification | Value |
|---------------|-------|
| Amazon 売れ筋ランキング | 洋書 - 219,149位 ( 洋書の売れ筋ランキングを見る ) Library Management - 82位 Information Systems - 97位 Data Mining - 227位 |
| おすすめ度 | 5つ星のうち4.3 132 レビュー |

## Images

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## Customer Reviews

### ⭐⭐⭐⭐⭐ Four Stars
*by R***N on 2018年3月9日にインドでレビュー済み*

The front page is featuring wrongly as geophysics.

### ⭐⭐⭐⭐⭐ Continues to lead introductions to data mining
*by R***7 on 2017年6月13日にアメリカ合衆国でレビュー済み*

I've read and reviewed the 1st, 2nd and now the 4th edition. The authors are genuine experts, at the front of their fields, and by adding new contributors have been able to both update existing topics as well as add authoritative treatments of new ones. I recommend this text to anyone seeking a serious introduction to data mining. The emphasis is practical rather than theoretical, but there are pointers to the theoretical literature for those wanting them. The practical emphasis serves those wanting such, and provides motivation and context for the approach. For those with the necessary mathematical, statistical and computing background there are certainly a plethora of more advanced treatments, but Witten et.al. may well be the best available introduction to the subject for almost everyone.

### ⭐⭐⭐⭐⭐ buen libro pero no tiene teoria
*by H***O on 2018年1月18日にメキシコでレビュー済み*

lo compré porque pensaba que la parte de deep learning estaba bien explicada, pero es similar a las versiones anteriores, en el sentido de que es demasiado practico, lo único realmente nuevo es el capítulo 9 de metodos probabilisticos.

## Frequently Bought Together

- Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems)
- Data Mining: Concepts and Techniques (The Morgan Kaufmann Series in Data Management Systems)
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

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*Product available on Desertcart Kazakhstan*
*Store origin: KZ*
*Last updated: 2026-10-25*