It provides a flexible architecture for scalable distributed training, is extensible to run over a wide range of hardware, and has a focus on health-care applications.

Apache SINGA has won the 2024 SIGMOD Systems Award [1] for the development of a distributed, efficient, scalable, and easy-to-use deep learning platform for large scale data analytics.

SINGA-Auto frees users from constructing the machine learning models, tuning the hyper-parameters, and optimizing the prediction accuracy and speed.

By leveraging the version history of pipeline components and workspace, MLCask can skip unchanged preprocessing steps to address the frequent retraining challenges.

This model selection algorithm is integrated non-intrusively into PostgreSQL via stored procedures with optimizations on execution latency and memory consumption.

Apache SINGA is used across applications in banking, education, finance, healthcare, real estate, software development, and other categories.

The Ng Teng Fong General Hospital[12] collaborated with the Apache SINGA team to develop an application for people diagnosed with pre-diabetes, a condition where blood glucose levels are higher than normal, but not high enough to be classified as diabetes.