NVIDIA RAPIDS is an open-source suite of GPU-accelerated data science and AI libraries. It leverages CUDA and significantly enhances the performance of core Python frameworks including Polars, pandas, scikit-learn and NetworkX. Chris Deotte is a Senior Data Scientist at NVIDIA and Jean-Francois Puget is the Director and a Distinguished Engineer at NVIDIA. Chris and Jean-Francois are also Kaggle Grandmasters, which is the highest rank a data scientist or machine learning practitioner can achieve on Kaggle, a competitive platform for data science challenges. In this episode, they join the podcast with Sean Falconer to talk about Kaggle, GPU-acceleration for data science applications, where they’ve achieved the biggest performance gains, the unexpected challenges with tabular data, and much more. Sean’s been an academic, startup founder, and Googler. He has published works covering a wide range of topics from AI to quantum computing. Currently, Sean is an AI Entrepreneur in Residence at Confluent where he works on AI strategy and thought leadership. You can connect with Sean on LinkedIn.   Please click here to see the transcript of this episode. Sponsorship inquiries: sponsor@softwareengineeringdaily.com The post NVIDIA RAPIDS and Open Source ML Acceleration with Chris Deotte and Jean-Francois Puget appeared first on Software Engineering Daily.