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Crab - A Python Framework for Building Recommendation Systems
Crab is a Python framework for building recommendation engines. It began as a Mahout alternative for Python developers and is being rewritten as a Scikit-learn submodule. Crab currently features collaborative filtering algorithms and evaluation metrics. Developers are working in sprints to optimize performance by integrating Numpy and migrating Crab to work as a Scikit in order to make it faster and more accessible to the scientific community.
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Crab - A Python Framework for Building Recommendation Systems
- 1. Crab A Python Framework for Building Recommendation Engines Marcel Caraciolo Ricardo Caspirro Bruno Melo @marcelcaraciolo @ricardocaspirro @brunomelo
- 2. What is Crab? A python framework for building recommendation engines A Scikit module for collaborative, content and hybrid filtering Mahout Alternative for Python Developers :D Open-Source under the BSD license https://github.com/muricoca/crab
- 3. When started ? Itbegan one year ago Community-driven, 4 members Since April,2011 the open-source labs Muriçoca incorporated it Since April,2011 rewritting it as sub-module of Scikit-learn https://github.com/muricoca/
- 4. Knowing Scikits Scikits areScipy Toolkits - independent and projects hosted under a common namespace. Scikits Image Scikits MlabWrap Scikits AudioLab Scikit Learn .... http://scikits.appspot.com/scikits
- 5. Knowing Scikits Scikit-Learn Machine Learning Algorithms + scientific Python packages (Numpy, Scipy and Matplotlib) http://scikit-learn.sourceforge.net/ Our goal: Incorporate the Crab as Scikit and part of it as submodule of Scikit-Learn
- 6. Why Recommendations ? Theworld is an over-crowded place !"#$%&'()$*+$,-$&.#'/0'&%)#)$1(,0#
- 7. Why Recommendations * +,&-.$/).#&0#/"1.#$%234(".# ? $/)#5(&6 7&.2.#"$4,#)$8 We are overloaded * 93((3&/.#&0#:&'3".;#5&&<.# $/)#:-.34#2%$4<.#&/(3/" Thousands of news articles and blog posts each day * =/#>$/&3;#?#@A#+B#4,$//"(.;# 2,&-.$/).#&0#7%&6%$:.# Millions of movies, books and music tracks online "$4,#)$8 Several Places, Offers and Events * =/#C"1#D&%<;#."'"%$(# Even Friends sometimes we are overloaded ! 2,&-.$/).#&0#$)#:"..$6".# Ask Charlie Sheen (@charliesheen)... ."/2#2&#-.#7"%#)$8
- 8. Why Recommendations ? Wereally need and consume only a few of them! “A lot of times, people don’t know what they want until you show it to them.” Steve Jobs “We are leaving the Information age, and entering into the Recommendation age.” Chris Anderson, from book Long Tail
- 9. Why Recommendations ? CanGoogle help ? Yes, but only when we really know what we are looking for But, what’s does it mean by “interesting” ? Can Facebook help ? Yes, I tend to find my friends’ stuffs interesting What if i had only few friends and what they like do not always attract me ? Can experts help ? Yes, but it won’t scale well. But it is what they like, not me! Exactly same advice!
- 10. Why Recommendations ? Recommendation Systems Systems designed to recommend to me something I may like
- 11. Why Recommendations ? ! "#$%"’ $"’ ( ’ ) *#*+ ) & , Recommendation Systems -+ + *#) . - #/ ’ ) 0 #) 1# ! 2’ 2 3&"+ ) 1 4’ 5, 6 7 ) , *% "& ’ 863 Graph Representation
- 12. The current Crab CollaborativeFiltering algorithms User-Based, Item-Based and Slope One Evaluation of the Recommender Algorithms Precision, Recall, F1-Score, RMSE Precision-Recall Charts
- 13. The current Crab Demo Movies Recommendation https://github.com/marcelcaraciolo/crab/blob/master/crab/tests/test_recommender.py
- 14. Why migrate ? OldCrab running only using Pure Python Recommendations demand heavy maths calculations and lots of processing Compatible with Numpy and Scipy libraries High Standard and popular scientific libraries optimized for scientific calculations in Python Scikits projects are amazing! Active Communities, Scientific Conferences and updated projects (e.g. scikit-learn) Turn the Crab framework visible for the community Join the scientific researchers and machine learning developers around the Globe coding with Python to help us in this project Be Fast and Furious
- 15. Why migrate ? Numpyoptimized with PyPy 2.x - 48.x Faster http://morepypy.blogspot.com/2011/05/numpy-in-pypy-status-and-roadmap.html
- 16. How are weworking ? Sprints, Online Discussions and Issues https://github.com/muricoca/crab/wiki/UpcomingEvents
- 17. Future Releases Planned Release 0.1 Collaborative Filtering Algorithms working, sample datasets to load and test Planned Release 0.11 Evaluation of Recommendation Algorithms and Database Models support Planned Release 0.12 Recommendation as Services with REST APIs ....
- 18. Join us! 1. Readour Wiki Page https://github.com/muricoca/crab/wiki/Developer-Resources 2. Check out our current sprints and open issues https://github.com/muricoca/crab/issues 3. Forks, Pull Requests mandatory 4. Join us at irc.freenode.net #muricoca or at our discussion list in work :(
- 19. Crab A Python Framework for Building Recommendation Engines https://github.com/muricoca/crab Marcel Caraciolo Ricardo Caspirro Bruno Melo @marcelcaraciolo @ricardocaspirro @brunomelo {marcel, ricardo,bruno}@muricoca.com