The Data Exchange with Ben Lorica

This week our special correspondent and editor Jenn Webb and I speak with Jike Chong and Cathy Chang, executives and seasoned leaders of data science teams. Our conversation is focused on their new book “How to Lead in Data Science”.
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Detailed show notes can be found on The Data Exchange web site.
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This week’s guests are Reza Hosseini, Staff Software Engineer, and Albert Chen, Staff Data Scientist, both at Linkedin. Reza and Albert are part of the team behind the new open source library Greykite, a flexible and fast library for time-series forecasting.
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Detailed show notes can be found on The Data Exchange web site.
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This week’s guest is Nicolas (Nic) Hohn, Chief Data Scientist, McKinsey/QuantumBlack Australia. Nic led a team of data scientists charged with helping America’s Cup winning team, Emirates Team New Zealand, test new designs for hydrofoils – important sailing boat components that could be modified based on rules set forth by race organizers. More precisely the QuantumBlack team used Ray RLlib to design an AI agent that could learn to sail the boat for a given design at an optimal speed, and this AI agent proved crucial during the design process.
Subscribe: Apple • Android • Spotify • Stitcher • Google • RSS.
Detailed show notes can be found on The Data Exchange web site.
Subscribe to The Gradient Flow Newsletter.

Hagay Lupesko, is VP Engineering at MosaicML, a startup that enables teams to easily train large AI models on their data and in their own secure environment. We discuss the the evolution of cloud based machine learning (from “traditional” ML through LLMs), his experience building machine learning applications at leading technology companies, and the need for companies to build their own custom foundation models.
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Detailed show notes can be found on The Data Exchange web site.

In this episode of The Data Exchange, I speak with Paco Nathan, author, teacher, and founder of Derwen.ai, a boutique consulting firm specializing in Data, ML, and AI. Paco consults with companies and speaks before audiences all over the world, and I plan to have him as a frequent guest on this podcast to draw on his observations of diverse organizations.
This particular conversation spanned many topics, including:

• Data Governance: Paco’s talk on the topic
• AutoML: Paco’s talk on the topic
• PyTorch and TensorFlow: posts we discussed - [1], [2]
• Reproducibility and feature selection
• The Streamlit open source project for ML app development, and Grus Law (“if you can think up something crazy and/or dangerous to do with notebooks, people are doing it.”)

I want this to be more than just a podcast. I want to create a community to help people make better decisions. A key part of this is getting you involved. I have ideas on how this community will grow, but as a first step, I want to ask a question related to one of the topics that Paco and I discussed: PyTorch and TensorFlow. I'd love to have you weigh in by filling out the survey form. I'll report on results and key insights in a future episode of this podcast.
[full show notes can be found on the Data Exchange site.]