Brian Tepera

Brian is a technical product manager on the RAPIDS team at NVIDIA, where he is focused on bringing accelerated computing to the Python data science ecosystem. Prior to NVIDIA, he worked in data and analytics at Dataminr and Capital One.
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Posts by Brian Tepera

Data Science

RAPIDS Adds GPU Polars Streaming, a Unified GNN API, and Zero-Code ML Speedups

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... 6 MIN READ
Data Science

How to Work with Data Exceeding VRAM in the Polars GPU Engine

In high-stakes fields such as quant finance, algorithmic trading, and fraud detection, data practitioners frequently need to process hundreds of gigabytes (GB)... 4 MIN READ
A diagram shows machine learning algorithms and the scikit-learn logo running on NVIDIA cuML to best leverage a system’s GPU and CPU.
Data Science

NVIDIA cuML Brings Zero Code Change Acceleration to scikit-learn

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... 8 MIN READ
Data Science

Accelerating Time Series Forecasting with RAPIDS cuML

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... 4 MIN READ