{"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 MLOps Teams Are Using Model Monitoring to Prevent Silent Failures","slug":"how-mlops-teams-are-using-model-monitoring-to-prevent-silent-failures","published_at":"2026-06-08T20:10:05+00:00","page_url":"https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-mlops-teams-are-using-model-monitoring-to-prevent-silent-failures","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-0039.mp3","audio_url":"https://audio.fexingo.com/business/the-data-science-podcast/episode-0039.mp3","summary":"Episode 39 of The Data Science Podcast explores the growing discipline of model monitoring in production. Lucas and Luna discuss why many data science teams still treat monitoring as an afterthought, how silent failures erode business trust, and what tools like Evidently AI, WhyLabs, and custom dashboards are doing about it. They walk through a real example from a fintech lending platform where a model drifted undetected for weeks, costing the company over $2 million in bad loans. The conversation also covers the three key pillars of monitoring: data quality, model performance, and operational health. Lucas shares a practical checklist for teams getting started with monitoring today. If you are deploying models to production, this episode will save you from waking up to a 3 AM pager alert. #ModelMonitoring #MLOps #DataScience #MachineLearning #ProductionML #SilentFailures #ConceptDrift #DataQuality #MLPipeline #Fintech #EvidentlyAI #WhyLabs #MLObservability #DataDrift #ModelGovernance #FexingoBusiness #BusinessPodcast #Technology Keep every episode free: buymeacoffee.com/fexingo","meta_description":"Episode 39 of The Data Science Podcast explores the growing discipline of model monitoring in production. Lucas and Luna discuss why many data science tea…","key_points":[],"chapters":[],"topics":[],"duration_seconds":523,"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-mlops-teams-are-using-model-monitoring-to-prevent-silent-failures/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-mlops-teams-are-using-model-monitoring-to-prevent-silent-failures.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}