logo
episode-header-image
Mar 2025
42m 6s

NVIDIA RAPIDS and Open Source ML Acceler...

Software Engineering Daily
About this episode

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.

Up next
Jul 8
SED News: Data Land Grabs, Copyright Fights, and the Great AI Talent War
Welcome back to SED News, a podcast series from Software Engineering Daily where hosts Gregor Vand and Sean Falconer break down the latest stories in software engineering, Silicon Valley, and the wider tech industry. In this episode, Gregor and Sean dig into Meta’s legal battle o ... Show More
46m 15s
Jul 3
AI at Anaconda with Greg Jennings
Anaconda is a software company that’s well-known for its solutions for managing packages, environments, and security in large-scale data workflows. The company has played a major role in making Python-based data science more accessible, efficient, and scalable. Anaconda has also ... Show More
49m 29s
Jul 1
ByteDance’s Container Networking Stack with Chen Tang
ByteDance is a global technology company operating a wide range of content platforms around the world, and is best known for creating TikTok. The company operates at a massive scale, which naturally presents challenges in ensuring performance and stability across its data centers ... Show More
47m 57s
Recommended Episodes
Nov 2024
SE Radio 641: Catherine Nelson on Machine Learning in Data Science
Catherine Nelson, author of the new O’Reilly book, Software Engineering for Data Scientists, discusses the collaboration between data scientists and software engineers -- an increasingly common pairing on machine learning and AI projects. Host Philip Winston speaks with Nelson ab ... Show More
48m 19s
Aug 2024
AI in Action: From Machine Learning Interpretability to Cybersecurity with Serg Masís and Nirmal Budhathoki
In this DSS Podcast, Anna Anisin welcomes Serg Masís, Climate and Agronomic Data Scientist at Syngenta. Serg, an expert in machine learning interpretability and responsible AI, shares his diverse background and journey into data science. He discusses the challenges of building fa ... Show More
25m 37s
Jan 2021
CNCF and the Linux Foundation, with Chris Aniszcyzk
After building the Eclipse IDE and Twitter’s Open Source office, Chris Aniszcyzk bootstrapped the CNCF, joining its parent the Linux Foundation in 2015. He’s now a VP of DevRel there, as well as CTO at the CNCF and Executive Director of the Open Container Initiative. Chris joins ... Show More
38m 40s
Jul 2024
#225 The Full Stack Data Scientist with Savin Goyal, Co-Founder & CTO at Outerbounds
The role of the data scientist is changing. Some organizations are splitting the role into more narrowly focused jobs, while others are broadening it. The latter approach, known as the Full Stack Data Scientist, is derived from the concept of a full stack software engineer, with ... Show More
48m 44s
Oct 2017
Data science tools and other announcements from Ignite
In this episode, Microsoft's Corporate Vice President for Cloud Artificial Intelligence, Joseph Sirosh, joins host Kyle Polich to share some of the Microsoft's latest and most exciting innovations in AI development platforms. Last month, Microsoft launched a set of three powerful ... Show More
31m 40s
Apr 2024
Measuring The Speed of AI Through Benchmarks
David Kanter, Executive Director at MLCommons, discusses the work they’re doing with MLPerf Benchmarks, creating the world’s first industry standard approach to measuring AI speed and safety. He also shares ways they’re testing AI and LLMs for harm, to measure—and, over time, red ... Show More
31m 45s
Nov 2024
scikit-learn & data science you own
We are at GenAI saturation, so let’s talk about scikit-learn, a long time favorite for data scientists building classifiers, time series analyzers, dimensionality reducers, and more! Scikit-learn is deployed across industry and driving a significant portion of the “AI” that is ac ... Show More
52m 2s
Oct 2024
Ep18. Jensen Recap - Competitive Moat, X.AI, Smart Assistant | BG2 w/ Bill Gurley & Brad Gerstner
Open Source bi-weekly convo w/ Bill Gurley and Brad Gerstner on all things tech, markets, investing & capitalism. This week, joined by Sunny Madra (Groq) they discuss Jensen Huang’s recent appearance on the podcast, including scaling intelligence towards AGI, NVIDIA's strategic p ... Show More
54m 6s
Feb 2022
Nick Singh - Ace the Data Science Interview #8
Our guest today is Nick Singh, ex-Facebook, Google, Microsoft and Author of "Ace the Data Science Interview", an Amazon best seller book which helps you land your dream Data Science job. In our conversation, we first talk about Nick's career in industry. We explore how he ma ... Show More
59m 12s
Aug 2024
#474: Python Performance for Data Science
Python performance has come a long way in recent times. And it's often the data scientists, with their computational algorithms and large quantities of data, who care the most about this form of performance. It's great to have Stan Seibert back on the show to talk about Python's ... Show More
1h 8m