Showing 1-8 of 8 projects
A Jupyter Notebook book that teaches linear algebra and machine learning concepts using the power of matrices.
A curated list of community detection research papers with implementations for data science and network analysis.
A Python library for building recommender systems using popular deep learning techniques like DeepFM, NCF, and more.
LAPACK is a comprehensive library for linear algebra computations including matrix factorizations.
An open-source toolkit for deep learning-based recommendation with TensorFlow.
Fast Clojure matrix library for high-performance linear algebra and numerical computing on CPU and GPU.
A fast, scalable library for Factorization Machines, a powerful machine learning model for recommendation systems.
A comparative framework for building multimodal recommender systems using collaborative filtering and matrix factorization.
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