This document provides an overview and introduction to the Apache Mahout machine learning library. It discusses how Mahout can be used to build scalable machine learning applications using algorithms like collaborative filtering, clustering, classification and frequent pattern mining. It also describes how Mahout can be used for recommendation engines and document classification. The document concludes with references and resources for learning more about Mahout.

1. Practical Machine Learning
A Tutorial on Apache Mahout
Biju B
NLP R&D Division
365Media Pvt. Ltd.
bijub@365Media.in
FOSSMEET NITC,
Calicut
4-6 February 2011
Biju B & Jaganadh G Practical Machine Learning

2. nlp r d $ whoweare
Working in Natural Language Processing (NLP), Machine Learning,
Data Mining
Passionate about Free and Open source :-)
When gets free time teaches Python and blogs at
http://jaganadhg.freeflux.net/blog and contributes to
Openstreetmap
Works for 365Media Pvt. Ltd. Coimbatore India.
twitter handle : @jaganadhg, @bijub
Biju B & Jaganadh G Practical Machine Learning

3. Machine Learning
Machine Learning
Machine learning is a subfield of artificial intelligence (AI) concerned with
algorithms that allow computers to learn.
Biju B & Jaganadh G Practical Machine Learning

4. Machine Learning
Machine Learning
Machine learning is a subfield of artificial intelligence (AI) concerned with
algorithms that allow computers to learn.
Biju B & Jaganadh G Practical Machine Learning

5. Machine Learning
Machine Learning
Machine learning is a subfield of artificial intelligence (AI) concerned with
algorithms that allow computers to learn.
This talk is not aimed to give introduction about Machine Learning
Biju B & Jaganadh G Practical Machine Learning

6. Machine Learning
Machine Learning
Machine learning is a subfield of artificial intelligence (AI) concerned with
algorithms that allow computers to learn.
This talk is not aimed to give introduction about Machine Learning
Dont expect some mathy equations here
Biju B & Jaganadh G Practical Machine Learning

7. Machine Learning and Our Life
Do you think that Machine Learning has any impact in our life ??
Biju B & Jaganadh G Practical Machine Learning

8. Machine Learning and Our Life
Do you think that Machine Learning has any impact in our life ??
Yes
Biju B & Jaganadh G Practical Machine Learning

9. Machine Learning and Our Life
Do you think that Machine Learning has any impact in our life ??
Yes
In our day to day life we may use many Machine Learning powered
tools
Biju B & Jaganadh G Practical Machine Learning

10. Machine Learning and Our Life
Do you think that Machine Learning has any impact in our life ??
Yes
In our day to day life we may use many Machine Learning powered
tools
Recommendation Engines
Biju B & Jaganadh G Practical Machine Learning

11. Machine Learning and Our Life
Do you think that Machine Learning has any impact in our life ??
Yes
In our day to day life we may use many Machine Learning powered
tools
Recommendation Engines
Clustering
Biju B & Jaganadh G Practical Machine Learning

12. Machine Learning and Our Life
Do you think that Machine Learning has any impact in our life ??
Yes
In our day to day life we may use many Machine Learning powered
tools
Recommendation Engines
Clustering
Classification , Spam Filtering
Biju B & Jaganadh G Practical Machine Learning

13. Machine Learning and Our Life
Do you think that Machine Learning has any impact in our life ??
Yes
In our day to day life we may use many Machine Learning powered
tools
Recommendation Engines
Clustering
Classification , Spam Filtering
Sentiment Analysis
Biju B & Jaganadh G Practical Machine Learning

14. Machine Learning and Our Life
Do you think that Machine Learning has any impact in our life ??
Yes
In our day to day life we may use many Machine Learning powered
tools
Recommendation Engines
Clustering
Classification , Spam Filtering
Sentiment Analysis
Fraud Detraction
Biju B & Jaganadh G Practical Machine Learning

15. Mahout
Mahout
Open Source project by Apache Foundation
Goal of this project is to build scalable machine learning libraries
Biju B & Jaganadh G Practical Machine Learning

16. Mahout
Mahout
Mahout: a person who drives elephant ;-)
The name comes from the project’s use of Apache Hadoop.
Biju B & Jaganadh G Practical Machine Learning

17. Why a new library ?
There are more than 30 Java libraries/ tools available for Machine
Learning.
Weka , Mallet, Classifier4j, Rapidminer ........
Large Amount of data processing is not an easy task
Machine Learning tools are supposed to produce quick results
If the amount of data is too large it is not easy to process with a
single machine (Even if it is powerful)
Mahout is scalable: the core algorithms in Mahout are implemented
on top of Apache Hadoop using the map/reduce paradigm
Biju B & Jaganadh G Practical Machine Learning

18. Algorithms in Apache Mahout
Biju B & Jaganadh G Practical Machine Learning

19. Algorithms in Apache Mahout
Collaborative Filtering
Biju B & Jaganadh G Practical Machine Learning

20. Algorithms in Apache Mahout
Collaborative Filtering
User and Item based recommenders
Biju B & Jaganadh G Practical Machine Learning

21. Algorithms in Apache Mahout
Collaborative Filtering
User and Item based recommenders
K-Means, Fuzzy K-Means clustering
Biju B & Jaganadh G Practical Machine Learning

22. Algorithms in Apache Mahout
Collaborative Filtering
User and Item based recommenders
K-Means, Fuzzy K-Means clustering
Mean Shift clustering
Biju B & Jaganadh G Practical Machine Learning

23. Algorithms in Apache Mahout
Collaborative Filtering
User and Item based recommenders
K-Means, Fuzzy K-Means clustering
Mean Shift clustering
Dirichlet process clustering
Biju B & Jaganadh G Practical Machine Learning

24. Algorithms in Apache Mahout
Collaborative Filtering
User and Item based recommenders
K-Means, Fuzzy K-Means clustering
Mean Shift clustering
Dirichlet process clustering
Latent Dirichlet Allocation
Biju B & Jaganadh G Practical Machine Learning

25. Algorithms in Apache Mahout
Collaborative Filtering
User and Item based recommenders
K-Means, Fuzzy K-Means clustering
Mean Shift clustering
Dirichlet process clustering
Latent Dirichlet Allocation
Singular value decomposition
Biju B & Jaganadh G Practical Machine Learning

26. Algorithms in Apache Mahout
Collaborative Filtering
User and Item based recommenders
K-Means, Fuzzy K-Means clustering
Mean Shift clustering
Dirichlet process clustering
Latent Dirichlet Allocation
Singular value decomposition
Parallel Frequent Pattern mining
Biju B & Jaganadh G Practical Machine Learning

27. Algorithms in Apache Mahout
Collaborative Filtering
User and Item based recommenders
K-Means, Fuzzy K-Means clustering
Mean Shift clustering
Dirichlet process clustering
Latent Dirichlet Allocation
Singular value decomposition
Parallel Frequent Pattern mining
Complementary Naive Bayes classifier
Biju B & Jaganadh G Practical Machine Learning

28. Algorithms in Apache Mahout
Collaborative Filtering
User and Item based recommenders
K-Means, Fuzzy K-Means clustering
Mean Shift clustering
Dirichlet process clustering
Latent Dirichlet Allocation
Singular value decomposition
Parallel Frequent Pattern mining
Complementary Naive Bayes classifier
Random forest decision tree based classifier
Biju B & Jaganadh G Practical Machine Learning

29. Recommendation
Filter information based on user preference
Searching a large set of people and finding a smaller set with tastes
similar to you
e.g :- Amazon’s book recommendation , Netflix movie
recommendation
Biju B & Jaganadh G Practical Machine Learning

30. Document Classification
Classify documents based on its content
e.g: - spam filtering,priority inbox
Biju B & Jaganadh G Practical Machine Learning

31. Demo
Building recommendations engines with Mahout
Document Classification with Mahout
Biju B & Jaganadh G Practical Machine Learning

32. Reference
Biju B & Jaganadh G Practical Machine Learning

33. Reference
Mahout in Action - Book by Sean Owen and Robin Anil, published
by Manning Publications.
Taming Text - By Grant Ingersoll and Tom Morton, published by
Manning Publications.
Introducing Apache Mahout - Grant Ingersoll - Intro to Apache
Mahout focused on clustering, classification and collaborative
filtering. https://www.ibm.com/developerworks/java/library/j-
mahout/index.html
Programming Collective Intelligence: Building Smart Web 2.0
Applications
http://www.amazon.com/Programming-Collective-Intelligence-
Building-Applications/dp/0596529325
Biju B & Jaganadh G Practical Machine Learning

34. Useful Resources
Apache Mahout Site http://mahout.apache.org/
Apache Mahout Mailing List user@mahout.apache.org
The code which I used for Mahout demo is available at
http://bitbucket.org/jaganadhg/blog/src/tip/bck9/java/
Twenty News Group data set
http://people.csail.mit.edu/jrennie/20Newsgroups/20news-
bydate.tar.gz
Biju B & Jaganadh G Practical Machine Learning

35. Questions ??
Biju B & Jaganadh G Practical Machine Learning

36. Acknowledgments
Thanks to :
Manning Publications for Review Copy of the book ”Mahout in
Action”
Apache Mahout mailing list members
Ted Dunning and Robin Anil for suggestions
@chelakkandupoda for review and criticism
Mukundhanchari R&D Director 365Media Pvt. Ltd. for support and
encouragement
Biju B & Jaganadh G Practical Machine Learning

37. Finally
Biju B & Jaganadh G Practical Machine Learning