Recommender alternatives and similar libraries
Based on the "Machine Learning" category.
Alternatively, view Recommender alternatives based on common mentions on social networks and blogs.
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mxnet
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more -
xgboost
Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow. [Apache2] -
Dlib
A general purpose cross-platform C++ library designed using contract programming and modern C++ techniques. [Boost] -
catboost
CatBoost is an open-source gradient boosting on decision trees library with categorical features support out of the box for Python, R -
Fido
A highly-modular C++ machine learning library for embedded electronics and robotics. [MIT] website -
sofia-ml
The suite of fast incremental algorithms for machine learning. [Apache2]
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README
Recommender 
A C library for product recommendations/suggestions using collaborative filtering (CF).
Recommender analyzes the feedback of some users (implicit and explicit) and their preferences for some items. It learns patterns and predicts the most suitable products for a particular user.
Features
- Collaborative Filtering
- User and Item based recommenders
- No external dependencies
- Fast running time ~ 81 seconds for 10 million ratings (on MovieLens Data Sets)
- Memory footprint under 160 MB for 10 million ratings
Webpage
http://ghamrouni.github.com/Recommender/
Building
To compile Recommender:
make
The compilation will produce libRecommender.a
To compile an example:
gcc test/test.c src/libRecommender.a -lm -o test/t1 -I src/
Alternatively you can use clang
clang test/test.c src/libRecommender.a -lm -o test/t1 -I src/
Keywords
Collaborative filtering, recommender system
References
*Note that all licence references and agreements mentioned in the Recommender README section above
are relevant to that project's source code only.