practical machine learning
DESCRIPTION
A talk on practical use of Machine Learning and MahoutTRANSCRIPT
Practical Machine Learning
Jaganadh [email protected]
BarCamp Kerala 9Amrita Vishwa Vidyapeetham
Karunagapally
14 November 2010
Jaganadh G Practical Machine Learning
About me !!
Working in Natural Language Processing, Machine Learning,Data Mining etc...
Passionate about Free and Open source :-)
When gets free time teaches Python and blogs athttp://jaganadhg.freeflux.net/blog
Working as Project Lead (NLP) 365Media Pvt. Ltd.Coimbatore
I am a computational linguist / Linguist and Indologist
Now Software Engineer by Profession
Jaganadh G Practical Machine Learning
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 MachineLearning
Dont expect some mathy equations here
Jaganadh G Practical Machine Learning
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 MachineLearning
Dont expect some mathy equations here
Jaganadh G Practical Machine Learning
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 MachineLearning
Dont expect some mathy equations here
Jaganadh G Practical Machine Learning
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 MachineLearning
Dont expect some mathy equations here
Jaganadh G Practical Machine Learning
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 Learningpowered tools
E-mail spam filtering , product recommendations etc ..
Fraud detection
Jaganadh G Practical Machine Learning
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 Learningpowered tools
E-mail spam filtering , product recommendations etc ..
Fraud detection
Jaganadh G Practical Machine Learning
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 Learningpowered tools
E-mail spam filtering , product recommendations etc ..
Fraud detection
Jaganadh G Practical Machine Learning
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 Learningpowered tools
E-mail spam filtering , product recommendations etc ..
Fraud detection
Jaganadh G Practical Machine Learning
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 Learningpowered tools
E-mail spam filtering , product recommendations etc ..
Fraud detection
Jaganadh G Practical Machine Learning
Examples
Jaganadh G Practical Machine Learning
Examples
Jaganadh G Practical Machine Learning
Examples
Jaganadh G Practical Machine Learning
Tool for building Machine Learning powerd product/service
Apache Mahout
Apache Mahout is a scalable machine learning library that supportslarge data sets. Apache Mahout’s goal is to build scalable machinelearning libraries.
Commercially friendly licence
Well documented
Healthy community
Targeted to developers
Jaganadh G Practical Machine Learning
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
Jaganadh G Practical Machine Learning
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
Jaganadh G Practical Machine Learning
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
Jaganadh G Practical Machine Learning
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
Jaganadh G Practical Machine Learning
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
Jaganadh G Practical Machine Learning
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
Jaganadh G Practical Machine Learning
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
Jaganadh G Practical Machine Learning
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
Jaganadh G Practical Machine Learning
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
Jaganadh G Practical Machine Learning
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
Jaganadh G Practical Machine Learning
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
Jaganadh G Practical Machine Learning
Demo
Building recommendations engines with Mahout
Document Classification with Mahout
Some Python stuff on Machine Learning
Jaganadh G Practical Machine Learning
Reference
Jaganadh G Practical Machine Learning
Reference
Mahout in Action - Book by Sean Owen and Robin Anil,published by Manning Publications.
Taming Text - By Grant Ingersoll and Tom Morton, publishedby Manning Publications.
Introducing Apache Mahout - Grant Ingersoll - Intro toApache Mahout focused on clustering, classification andcollaborative filtering.https://www.ibm.com/developerworks/java/library/j-mahout/index.html
Programming Collective Intelligence: Building Smart Web 2.0Applicationshttp://www.amazon.com/Programming-Collective-Intelligence-Building-Applications/dp/0596529325
Jaganadh G Practical Machine Learning
Useful Resources
Apache Mahout Site http://mahout.apache.org/
Apache Mahout Mailing List [email protected]
The code which I used for Mahout demo is available athttp://bitbucket.org/jaganadhg/blog/src/tip/bck9/java/
Twenty News Group data sethttp://people.csail.mit.edu/jrennie/20Newsgroups/20news-bydate.tar.gz
Jaganadh G Practical Machine Learning
Questions ??
Jaganadh G Practical Machine Learning
Acknowledgments
Thanks to :
Manning Publications for Review Copy of the book ”Mahoutin Action”
Apache Mahout mailing list members
Ted Dunning and Robin Anil for suggestions
Sreejith S and Biju B for Java help
@chelakkandupoda for review and criticism
Mukundhanchari R&D Director 365Media Pvt. Ltd. forsupport and encouragement
Jaganadh G Practical Machine Learning
Finally
Jaganadh G Practical Machine Learning