Episodes
Active Learning in ML, DataPrepOps, Carbon footprint of AI systems | Jennifer PrendkiAugust 01, 2022
Telling stories WITH data vs ABOUT data | Scott TaylorJuly 28, 2022
Upskilling, learning, and keeping yourself relevant as a data practitioner | Matt HarrisonJuly 25, 2022
Ben Taylor on metaheuristics, AI teaching AI, genetic programming, impact of generative AI on art, building startups, and what it means to be the first data scientist at a companyJuly 21, 2022
Srinath Sridhar on the 0-to-1 journey of building ML productsJuly 18, 2022
What's new in ML: Space telescope, rare earth elements, universal speech translator, quantitative reasoning, quantum computing, robots handling deformable material, and how AI systems can explain a piece of code.July 14, 2022
Adam Sroka on how energy markets work, where renewable energy fits in, software engineering, data scientists, and using machine learning for climate problemsJuly 11, 2022
Doug Laney on infonomics, data monetization patterns, quantifying data's economic value, collateralizing data, and insuring data.July 06, 2022
What's new in ML: The question of whether AI is sentient, NASA's helicopter on Mars, Yann LeCun's recent proposal on Autonomous Machine Intelligence, Amazon's AI-powered coding assistant, and a reconfigurable AI chip built by MIT engineers.June 29, 2022
Jason Krantz on talent trends in the AI sector, hyperlocal job markets in US, flow of talent across sectors, and the craft of employee retentionJune 26, 2022
Jordan Morrow on the next unlock for the education market, data literacy, and upskilling in machine learningJune 19, 2022
Harpreet Sahota on community building, bottom-up adoption, and developer relations for machine learning productsJune 19, 2022
Brent Dykes on data storytellingJune 15, 2022
Joe Reis on data engineering and architectureJune 12, 2022
What's new in ML: Prateek Joshi talks about nuclear fusion, photonic chips, electronic skin, and analyzing satellite imagery with machine learning.June 09, 2022
Vin Vashishta on injecting reality into machine learning products and creating business value with data scienceJune 05, 2022
AMA with Prateek Joshi: Space industry, synthetic data in machine learning, foundation models, AI-infused coding toolsJune 01, 2022
Serg Masis on interpretable machine learning, process fairness vs statistical fairness, how to measure interpretability, how to interpret neural networks, how to increase the interpretability of a modelMay 29, 2022
AMA with Prateek Joshi: Python vs Matlab for machine learning, switching careers to ML, building startups, career pathsMay 25, 2022
Zach Keller on recommerce, circular shopping, carbon footprint, economics, how do incentives work in marketplaces, push bucket vs pull bucket, machine learning tools, building data science cultureMay 22, 2022
What's new in ML: Prateek Joshi talks about predicting battery lifetimes, fighting wildfires with machine learning, rainfall mapping, avoiding idling at traffic lights, world's largest publicly available machine learning hub, a plant nutrient detected by May 18, 2022
Demetrios Brinkmann and Vishnu Rachakonda on how they built the world's largest online hub for production Machine Learning practitionersMay 15, 2022
What's new in ML: Prateek Joshi talks about brain computer interface, nanomagnetic computing, counting microplastics using Machine Learning, quantum tunneling memory, wine reviews written by AI, spotting cavity, cancer researchMay 11, 2022
Thom Ives on his AI journey, creating educational content, establishing online presence, building a portfolio of machine learning projects, preventing burnout, how growth happens through cycles, storytelling for data scientists.May 08, 2022
What's new in ML: Prateek Joshi talks about generative AI, enzyme that can break down plastic quickly, nuclear fusion, low-carbon concrete, synthesizing molecules, object detection, few-shot learning.May 04, 2022
Telling stories WITH data vs ABOUT data | Scott TaylorJuly 28, 2022
Upskilling, learning, and keeping yourself relevant as a data practitioner | Matt HarrisonJuly 25, 2022
Ben Taylor on metaheuristics, AI teaching AI, genetic programming, impact of generative AI on art, building startups, and what it means to be the first data scientist at a companyJuly 21, 2022
Srinath Sridhar on the 0-to-1 journey of building ML productsJuly 18, 2022
What's new in ML: Space telescope, rare earth elements, universal speech translator, quantitative reasoning, quantum computing, robots handling deformable material, and how AI systems can explain a piece of code.July 14, 2022
Adam Sroka on how energy markets work, where renewable energy fits in, software engineering, data scientists, and using machine learning for climate problemsJuly 11, 2022
Doug Laney on infonomics, data monetization patterns, quantifying data's economic value, collateralizing data, and insuring data.July 06, 2022
What's new in ML: The question of whether AI is sentient, NASA's helicopter on Mars, Yann LeCun's recent proposal on Autonomous Machine Intelligence, Amazon's AI-powered coding assistant, and a reconfigurable AI chip built by MIT engineers.June 29, 2022
Jason Krantz on talent trends in the AI sector, hyperlocal job markets in US, flow of talent across sectors, and the craft of employee retentionJune 26, 2022
Jordan Morrow on the next unlock for the education market, data literacy, and upskilling in machine learningJune 19, 2022
Harpreet Sahota on community building, bottom-up adoption, and developer relations for machine learning productsJune 19, 2022
Brent Dykes on data storytellingJune 15, 2022
Joe Reis on data engineering and architectureJune 12, 2022
What's new in ML: Prateek Joshi talks about nuclear fusion, photonic chips, electronic skin, and analyzing satellite imagery with machine learning.June 09, 2022
Vin Vashishta on injecting reality into machine learning products and creating business value with data scienceJune 05, 2022
AMA with Prateek Joshi: Space industry, synthetic data in machine learning, foundation models, AI-infused coding toolsJune 01, 2022
Serg Masis on interpretable machine learning, process fairness vs statistical fairness, how to measure interpretability, how to interpret neural networks, how to increase the interpretability of a modelMay 29, 2022
AMA with Prateek Joshi: Python vs Matlab for machine learning, switching careers to ML, building startups, career pathsMay 25, 2022
Zach Keller on recommerce, circular shopping, carbon footprint, economics, how do incentives work in marketplaces, push bucket vs pull bucket, machine learning tools, building data science cultureMay 22, 2022
What's new in ML: Prateek Joshi talks about predicting battery lifetimes, fighting wildfires with machine learning, rainfall mapping, avoiding idling at traffic lights, world's largest publicly available machine learning hub, a plant nutrient detected by May 18, 2022
Demetrios Brinkmann and Vishnu Rachakonda on how they built the world's largest online hub for production Machine Learning practitionersMay 15, 2022
What's new in ML: Prateek Joshi talks about brain computer interface, nanomagnetic computing, counting microplastics using Machine Learning, quantum tunneling memory, wine reviews written by AI, spotting cavity, cancer researchMay 11, 2022
Thom Ives on his AI journey, creating educational content, establishing online presence, building a portfolio of machine learning projects, preventing burnout, how growth happens through cycles, storytelling for data scientists.May 08, 2022
What's new in ML: Prateek Joshi talks about generative AI, enzyme that can break down plastic quickly, nuclear fusion, low-carbon concrete, synthesizing molecules, object detection, few-shot learning.May 04, 2022