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What is Rapids and why should you care?

This includes a familiar DataFrame API that integrates with a variety of machine learning algorithms for end-to-end pipeline accelerations without paying typical serialization costs. RAPIDS also includes support for multi-node, multi-GPU deployments, enabling vastly accelerated processing and training on much larger dataset sizes.

What speed can I expect from Rapids?

Users can expect typical speedups of 10X or greater. RAPIDS’s machine learning algorithms and mathematical primitives follow a familiar scikit-learn-like API. Popular tools like XGBoost, Random Forest, and many others are supported for both single GPU and large data center deployments.

Why data science with rapids?

Data science is all about speed to results. RAPIDS leverages NVIDIA CUDA ® under the hood to accelerate your workflows by running the entire data science training pipeline on GPUs. This reduces training time and the frequency of model deployment from days to minutes.

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