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NVIDIA Merlin is an open-source library that accelerates recommender systems on NVIDIA GPUs. The library enables data scientists, machine learning engineers, and researchers to build high-performing recommenders at scale. Merlin includes tools to address common feature engineering, training, and inference challenges. Each stage of the Merlin pipeline is optimized to support hundreds of terabytes of data, which is all accessible through easy-to-use APIs. For more information, see NVIDIA Merlin on the NVIDIA developer website. Transform data (ETL) for preprocessing and engineering features. Accelerate your existing training pipelines in TensorFlow, PyTorch, or FastAI by leveraging optimized, custom-built data loaders. Scale large deep learning recommender models by distributing large embedding tables that exceed available GPU and CPU memory. Deploy data transformations and trained models to production with only a few lines of code.
Features
- Transform data (ETL) for preprocessing and engineering features
- Accelerate your existing training pipelines in TensorFlow, PyTorch, or FastAI by leveraging optimized, custom-built data loaders
- Scale large deep learning recommender models by distributing large embedding tables that exceed available GPU and CPU memory
- Deploy data transformations and trained models to production with only a few lines of code
- NVTabular is a feature engineering and preprocessing library for tabular data
- HugeCTR is a GPU-accelerated training framework that can scale large deep learning recommendation models
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