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NVIDIA-Certified Associate Generative AI LLM
A data science team runs machine learning algorithms using scikit-learn but is hitting long training times on large datasets. They want to accelerate execution on GPUs while continuing to use their existing scikit-learn code unchanged. Which CUDA-X library best fits this need?
Explanation
cuDF is a toolkit that contains GPU-accelerated libraries to optimize fundamental DataFrame operations.
cuML is a GPU-accelerated machine learning library that optimizes machine learning algorithms for execution on GPUs. It includes accelerators that run machine learning algorithms in
An enterprise wants to accelerate their existing Apache Spark data preprocessing pipeline on NVIDIA GPUs but is concerned about the engineering effort required to modify pipeline code. Which statement accurately reflects the RAPIDS Accelerator for Apache Spark?
Explanation
The RAPIDS™ Accelerator for Apache Spark is a plug-in that leverages RAPIDS libraries and GPUs to accelerate data processing and machine learning pipelines on Apache
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