Practical Machine Learning
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The document summarizes Jaganadh G's presentation on practical machine learning. It introduces Jaganadh and his background in natural language processing and machine learning. It then discusses machine learning and how it impacts daily life through applications like email spam filtering and product recommendations. The presentation provides an overview of the Apache Mahout machine learning library and its algorithms. It includes demos of building recommendation engines and document classification with Mahout.
Practical Machine Learning
- 1. Practical Machine Learning Jaganadh G jaganadhg@gmail.com BarCamp Kerala 9 Amrita Vishwa Vidyapeetham Karunagapally 14 November 2010 Jaganadh G Practical Machine Learning
- 2. 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 at http://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
- 3. Machine Learning Machine Learning Machine learning is a subfield of artificial intelligence (AI) concerned with algorithms that allow computers to learn. 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. 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 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 Jaganadh G Practical Machine Learning
- 7. Machine Learning and Our Life Do you think that Machine Learning has any impact in our life ?? Jaganadh G Practical Machine Learning
- 8. Machine Learning and Our Life Do you think that Machine Learning has any impact in our life ?? Yes 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 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 E-mail spam filtering , product recommendations etc .. 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 E-mail spam filtering , product recommendations etc .. Fraud detection Jaganadh G Practical Machine Learning
- 12. Examples Jaganadh G Practical Machine Learning
- 13. Examples Jaganadh G Practical Machine Learning
- 14. Examples Jaganadh G Practical Machine Learning
- 15. Tool for building Machine Learning powerd product/service Apache Mahout Apache Mahout is a scalable machine learning library that supports large data sets. Apache Mahout’s goal is to build scalable machine learning libraries. Commercially friendly licence Well documented Healthy community Targeted to developers Jaganadh G Practical Machine Learning
- 16. Algorithms in Apache Mahout Jaganadh G Practical Machine Learning
- 17. Algorithms in Apache Mahout Collaborative Filtering Jaganadh G Practical Machine Learning
- 18. Algorithms in Apache Mahout Collaborative Filtering User and Item based recommenders Jaganadh G Practical Machine Learning
- 19. Algorithms in Apache Mahout Collaborative Filtering User and Item based recommenders K-Means, Fuzzy K-Means clustering Jaganadh G Practical Machine Learning
- 20. Algorithms in Apache Mahout Collaborative Filtering User and Item based recommenders K-Means, Fuzzy K-Means clustering Mean Shift clustering Jaganadh G Practical Machine Learning
- 21. Algorithms in Apache Mahout Collaborative Filtering User and Item based recommenders K-Means, Fuzzy K-Means clustering Mean Shift clustering Dirichlet process clustering 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 Dirichlet process clustering Latent Dirichlet Allocation 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 Latent Dirichlet Allocation Singular value decomposition 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 Singular value decomposition Parallel Frequent Pattern mining 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 Parallel Frequent Pattern mining Complementary Naive Bayes classifier 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 Complementary Naive Bayes classifier Random forest decision tree based classifier Jaganadh G Practical Machine Learning
- 27. Demo Building recommendations engines with Mahout Document Classification with Mahout Some Python stuff on Machine Learning Jaganadh G Practical Machine Learning
- 28. Reference Jaganadh G Practical Machine Learning
- 29. 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 Jaganadh G Practical Machine Learning
- 30. 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 Jaganadh G Practical Machine Learning
- 31. Questions ?? Jaganadh G Practical Machine Learning
- 32. 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 Sreejith S and Biju B for Java help @chelakkandupoda for review and criticism Mukundhanchari R&D Director 365Media Pvt. Ltd. for support and encouragement Jaganadh G Practical Machine Learning
- 33. Finally Jaganadh G Practical Machine Learning