Navigating Advanced Data Science Techniques

With AI agents and GPU acceleration at the forefront, data science is entering a new era of efficiency and innovation. How are AI copilots transforming the way data scientists code and solve problems? Are they a reliable partner or a source of new complexities? On the other hand, the move to GPU-accelerated data science tools is revolutionizing model training and experimentation. What does this mean for the future of data science workflows? Explore these cutting-edge developments and their impact on the industry.

Jean-Francois got a PhD in machine learning in the previous millennium. Given the AI winter at the time, he worked for a while on mathematical optimization software as dev manager for CPLEX in a startup. He came back to Machine Learning when IBM acquired the startup. Since then he discovered Kaggle and became one of the best Kagglers in the world. He joined NVIDIA 5 years ago and leads the NVIDIA Kaggle Grandmaster team there.

Chris Deotte is a senior data scientist at NVIDIA. Chris has a Ph.D. in computational science and mathematics with a thesis on optimizing parallel processing. Chris is a Kaggle 4x grandmaster.

In the episode, Richie, Jean-Francois, and Chris explore the transformative role of AI agents in data science, the impact of GPU acceleration on workflows, the evolution of competitive data science techniques, the importance of model evaluation and communication skills, and the future of data science roles in an AI-driven world, and much more.

Links Mentioned in the Show:

• NVIDIA
• NVIDIA Rapids
• Few shot learning
• Connect with Jean-Francois on Linkedin and Kaggle and check out Chris on Kaggle
• Course: Winning a Kaggle Competition in Python
• Related Episode: Becoming a Kaggle Grandmaster
• Sign up to attend RADAR: Skills Edition

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