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16 Best Data Mining Books

Goal: Find the best Data Mining books according to the internet (not just one person's opinion).

Method:

  1. Search for "best data mining books" and study the top 5+ pages.
  2. Add only the books mentioned 2+ times.
  3. Rank the results neatly here.

16 Best Data Mining Books

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1

Introduction to Data Mining

by Pang-Ning Tan

2

Data Mining

Practical Machine Learning Tools and Techniques

by Ian H. Witten

3

Data Mining

The Textbook

by Charu C. Aggarwal

4

Data Mining Techniques

For Marketing, Sales, and Customer Relationship Management

by Gordon S. Linoff

5

Data Science for Business

What You Need to Know about Data Mining and Data-Analytic Thinking

by Foster Provost

6

The Elements of Statistical Learning

Data Mining, Inference, and Prediction

by Trevor Hastie

Also recommended by:

Nassim Taleb

7

A Programmer's Guide to Data Mining

by Ron Zacharski

8

Data Mining with Rattle and R

The Art of Excavating Data for Knowledge Discovery

by Graham Williams

9

Mining of Massive Datasets

by Jure Leskovec

10

Mining the Social Web

Data Mining Facebook, Twitter, LinkedIn, Instagram, GitHub, and More

by Matthew A. Russell

11

An Introduction to Statistical Learning

with Applications in R

by Daniela Witten

12

Bayesian Methods for Hackers

Probabilistic Programming and Bayesian Inference

by Cameron Davidson-Pilon

13

Big Data, Data Mining, and Machine Learning

Value Creation for Business Leaders and Practitioners

by Jared Dean

14

Data Mining

Concepts and Techniques

by Jiawei Han

15

Inductive Logic Programming

by Filip Železný

16

Modeling with Data

Tools and Techniques for Scientific Computing

by Ben Klemens

Sources

Edited by

Richard Reis

Software engineer whose passion for tracking book recommendations from podcasts inspired the creation of MRB.

Anurag Ramdasan

Lead investor at 3one4 Capital whose startup expertise and love for books helped shaped MRB and its growth.

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