{"podcast":{"title":"The Data Science Podcast with Fexingo: Analytics, Machine Learning, and Data-Driven Conversations","slug":"the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831","podcast_index_feed_id":7871831,"rss_url":"https://feeds.fexingo.com/business/the-data-science-podcast.xml","website_url":"https://www.fexingo.com/","image_url":"https://audio.fexingo.com/business/the-data-science-podcast/cover.png","author":"Fexingo","episode_count":118,"summary":"Lucas and Luna sit at a data-science workstation, two thin laptops open to scatter plots and clustering visualizations, and ask: what can we actually learn from the numbers? Each episode of The Data Science Podcast with Fexingo is a grounded, specific conversation about a single analytics problem or machine-learning method — from regularization in regression to the bias-variance trade-off in random forests. Lucas leads with a journalistic eye for how models are built and tested in the real world, citing actual case studies like how Netflix used matrix factorization for recommendations or how healthcare researchers apply survival analysis to clinical trials. Luna keeps the discussion honest, asking about data quality, feature engineering pitfalls, and whether a model’s accuracy actually translates to business value. They never resort to buzzwords: instead, they walk through the workflow from data collection to deployment, discussing trade-offs like interpretability versus performance. The show serves data scientists, analysts, and engineers who want to stay sharp on methods without the hype. Listeners walk away with a clearer understanding of why one algorithm beats another on a gi…","last_synced_at":"2026-07-19T08:17:23.323447+00:00","page_url":"https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831"},"episode":{"title":"How Data Scientists Use Counterfactual Explanations to Build Trust","slug":"how-data-scientists-use-counterfactual-explanations-to-build-trust","published_at":"2026-06-11T20:28:46+00:00","page_url":"https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-counterfactual-explanations-to-build-trust","show_page_url":"https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831","url":"https://audio.fexingo.com/business/the-data-science-podcast/episode-0045.mp3","audio_url":"https://audio.fexingo.com/business/the-data-science-podcast/episode-0045.mp3","summary":"Episode 45 of The Data Science Podcast explores the emerging practice of counterfactual explanations — 'what-if' scenarios that help end users understand why a machine learning model made a particular decision. Lucas and Luna walk through a concrete example from the lending industry: a small business owner named Maria whose loan application was denied by an automated risk model. Instead of a black-box rejection, a counterfactual explanation tells her: 'If your annual revenue were $150,000 instead of $100,000, your application would have been approved.' The hosts discuss how companies like JPMorgan and Zest AI are piloting these techniques to comply with regulatory pressure and improve customer trust, and they weigh the trade-offs between fidelity and simplicity. They also touch on the computational cost of generating counterfactuals at scale and the risk of exposing sensitive model boundaries. This episode is anchored to the current regulatory landscape as of June 2026, with references to the EU's AI Act and the FTC's guidance on algorithmic fairness. #CounterfactualExplanations #ExplainableAI #MachineLearning #DataScience #LendingAlgorithms #ModelInterpretability #AITrust #RegulatoryCompliance #EUAIAct #FTC #JPMorgan #ZestAI #SmallBusinessLoans #WhatIfAnalysis #BlackBoxModels #AlgorithmicFairness #FeatureImportance #FexingoBusiness Keep every episode free: buymeacoffee.com/fexingo","meta_description":"Episode 45 of The Data Science Podcast explores the emerging practice of counterfactual explanations — 'what-if' scenarios that help end users understand…","key_points":[],"chapters":[],"topics":[],"duration_seconds":515,"processing_state":"not_requested","actions":[{"name":"request_transcript","method":"POST","url":"https://stenobird.com/v1/public/podcasts/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/episodes/how-data-scientists-use-counterfactual-explanations-to-build-trust/transcription-requests","description":"Idempotently request low-priority transcript generation for this episode."},{"name":"read_markdown","method":"GET","url":"https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-counterfactual-explanations-to-build-trust.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}