Recommender Systems
Showing 17 of 17 projects
A Python library for building custom machine learning models for tasks like image classification, object detection, and recommendations.
A Python scikit for building and analyzing recommender systems that handle explicit rating data.
A unified, comprehensive, and efficient Python/PyTorch library for reproducing and developing recommendation algorithms.
Fast Python library for collaborative filtering recommendation algorithms on implicit feedback datasets.
An end-to-end platform for applied reinforcement learning and contextual bandits, built with PyTorch for production decision-making systems.
An end-to-end platform for applied reinforcement learning and contextual bandits, originally developed at Facebook for production recommendation systems.
A TensorFlow library for Learning-to-Rank (LTR) techniques, providing loss functions, metrics, and models for ranking tasks.
A TensorFlow library for building, training, and deploying recommender system models with Keras.
A software implementation of factorization machines for estimating interactions between categorical variables in large datasets.
A Python library implementing Factorization Machines with a scikit-learn compatible API for regression, classification, and ranking tasks.
A comparative Python framework for building, evaluating, and deploying multimodal recommender systems with auxiliary data.
TensorFlow implementation of arbitrary order (≥2) Factorization Machines for classification and regression tasks.
A Python library providing evaluation metrics and diagnostic tools for recommender systems.
Open-source teaching materials for a practical Machine Learning in Finance course, focusing on industry tools and real-world use cases.
A framework for building scalable machine learning models in Hadoop using the Scalding DSL.
A Python library providing comprehensive metrics for fair and thorough evaluation of recommender systems.
A Python toolbox using deep belief networks for topic modeling on document data, producing latent representations for content-based recommendation.
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