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Event DataFramed 2025-06-02
Dan Hannah – Associate Director @ SES AI Corporation , Richie – host @ DataCamp , Nick Becker – Group Product Manager @ NVIDIA

GPU acceleration is transforming how data scientists tackle computationally intensive problems in the AI and materials science fields. When dealing with billions of potential molecular combinations or massive datasets requiring dimensionality reduction, traditional CPU approaches often become prohibitively slow and expensive. How can data professionals determine when GPU acceleration will provide meaningful benefits to their workflows? Understanding the right applications for this technology can mean the difference between waiting hours versus minutes for critical results. Nick Becker is a Group Product Manager at NVIDIA, focused on building RAPIDS and the broader accelerated data science ecosystem. Nick has a professional background in technology and government. Prior to NVIDIA, he worked at Enigma Technologies, a data science startup. Before Enigma, he conducted economics research and forecasting at the Federal Reserve Board of Governors, the central bank of the United States. Dan Hannah is an Associate Director at SES AI Corporation. At SES, Dan leads a research program focused on discovering new battery materials using machine learning, chemical informatics, and physics-driven simulations. Prior to joining SES, Dan spent several years as a data scientist in the cybersecurity industry. Dan holds a Ph.D. in Physical Chemistry from Northwestern University and did a postdoctoral fellowship at Berkeley National Lab, where his focus was the discovery of novel inorganic materials for energy applications. In the episode, Richie, Nick, and Dan explore the quest for new battery technologies, the role of data science and machine learning in material discovery, the integration of NVIDIA's GPU technology, the balance between computational simulations and lab work, and much more. Links Mentioned in the Show: NVIDIA RAPIDSSES AI CorporationConnect with Dan and NickCareer Track: Machine Learning Scientist in PythonRelated Episode: Data Science Trends from 2 Kaggle Grandmasters with Jean-Francois Puget, Distinguished Engineer at NVIDIA & Chris Deotte, Senior Data Scientist at NVIDIARewatch sessions from RADAR: Skills Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

AI/ML Data Science
Dan Becker – CEO @ decision.ai , Adel – host @ DataFramed

In this episode of DataFramed, Adel speaks with Dan Becker, CEO of decision.ai and founder of Kaggle Learn on the intersection of decision sciences and AI, and best practices when aligning machine learning to business value.

Throughout the episode, Dan deep-dives into his background, how he reached the top of a Kaggle competition, the difference between machine learning in a Kaggle competition and the real world, the role of empathy when aligning machine learning to business value, the importance of decisions sciences when maximizing the value of machine learning in production, and more. 

Links:

Follow Dan on TwitterFollow Dan on LinkedInWhat 70% of data science learners do wrongCheck out Dan’s course on DataCampdecision.aiDan’s climate dashboard

AI/ML Dashboard Data Science
Dan Becker – CEO @ decision.ai

We talked about:

How we make decisions with machine learning What is decision optimization  Specifying the decision function Emulation for making the best decisions Decision optimization and reinforcement learning Getting started with decision optimization Trends in the industry

Links:

https://datatalks.club/people/danbecker.html https://www.decision.ai/​

Join DataTalks.Club: https://datatalks.club/slack.html

AI/ML HTML
DataTalks.Club
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