Search Results for "recommendation system"

...SparrowRecSys supports a wide range of state-of-the-art recommendation algorithms, including models for click-through rate prediction and user behavior modeling that are widely used in advertising and content recommendation systems. The system is designed as a modular platform combining technologies such as Spark, TensorFlow, and web server components to represent the full lifecycle of recommendation pipelines.

Deep-Learning-for-Recommendation-Systems is a curated repository that aggregates research papers, articles, and code related to deep learning methods for recommender systems. The project organizes influential academic work covering topics such as collaborative filtering, neural recommendation models, and deep feature learning. It includes references to papers describing architectures like collaborative deep learning, neural autoregressive models, and convolutional approaches to...

...The project aims to help developers and data scientists understand how distributed machine learning algorithms are implemented and optimized inside the Spark ecosystem. Instead of providing a runnable software system, the repository focuses on explaining algorithm principles and examining the underlying source code used in Spark’s machine learning package. The repository contains detailed analyses of various algorithms including classification, regression, clustering, dimensionality reduction, and recommendation systems. Each section discusses both the mathematical principles behind the algorithms and how Spark implements them in a distributed computing environment. ...