Brian Tepera – NVIDIA Technical Blog News and tutorials for developers, data scientists, and IT admins 2025-07-03T20:55:47Z http://www.open-lab.net/blog/feed/ Brian Tepera <![CDATA[RAPIDS Adds GPU Polars Streaming, a Unified GNN API, and Zero-Code ML Speedups]]> http://www.open-lab.net/blog/?p=102964 2025-07-03T20:55:47Z 2025-07-03T20:55:39Z RAPIDS, a suite of NVIDIA CUDA-X libraries for Python data science, released version 25.06, introducing exciting new features. These include a Polars GPU...]]>

RAPIDS, a suite of NVIDIA CUDA-X libraries for Python data science, released version 25.06, introducing exciting new features. These include a Polars GPU streaming engine, a unified API for graph neural networks (GNNs), and acceleration for support vector machines with zero code changes required. In this blog post, we’ll explore a few of these updates. In September 2024…

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Brian Tepera <![CDATA[How to Work with Data Exceeding VRAM in the Polars GPU Engine]]> http://www.open-lab.net/blog/?p=102715 2025-06-30T21:20:48Z 2025-06-27T17:00:00Z In high-stakes fields such as quant finance, algorithmic trading, and fraud detection, data practitioners frequently need to process hundreds of gigabytes (GB)...]]>

In high-stakes fields such as quant finance, algorithmic trading, and fraud detection, data practitioners frequently need to process hundreds of gigabytes (GB) of data to make quick, informed decisions. Polars, one of the fastest-growing data processing libraries, meets this need with a GPU engine powered by NVIDIA cuDF that accelerates compute-bound queries that are common in these fields.

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Brian Tepera <![CDATA[NVIDIA cuML Brings Zero Code Change Acceleration to scikit-learn]]> http://www.open-lab.net/blog/?p=97091 2025-04-23T00:22:52Z 2025-03-18T17:42:25Z Scikit-learn, the most widely used ML library, is popular for processing tabular data because of its simple API, diversity of algorithms, and compatibility with...]]>

Scikit-learn, the most widely used ML library, is popular for processing tabular data because of its simple API, diversity of algorithms, and compatibility with popular Python libraries such as pandas and NumPy. NVIDIA cuML now enables you to continue using familiar scikit-learn APIs and Python libraries while enabling data scientists and machine learning engineers to harness the power of CUDA on…

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Brian Tepera <![CDATA[Accelerating Time Series Forecasting with RAPIDS cuML]]> http://www.open-lab.net/blog/?p=95127 2025-01-23T19:54:21Z 2025-01-16T17:20:10Z Time series forecasting is a powerful data science technique used to predict future values based on data points from the past Open source Python libraries like...]]>

Time series forecasting is a powerful data science technique used to predict future values based on data points from the past Open source Python libraries like skforecast make it easy to run time series forecasts on your data. They allow you to “bring your own” regressor that is compatible with the scikit-learn API, giving you the flexibility to work seamlessly with the model of your choice.

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