{"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 MLOps to Keep Models in Production","slug":"how-data-scientists-use-mlops-to-keep-models-in-production","published_at":"2026-06-20T08:23:45+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-mlops-to-keep-models-in-production","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-0062.mp3","audio_url":"https://audio.fexingo.com/business/the-data-science-podcast/episode-0062.mp3","summary":"Episode 62 of The Data Science Podcast dives into the operational side of machine learning: MLOps. Lucas and Luna explore why so many models never make it to production, and how tools like feature stores, model registries, and automated pipelines keep deployed models accurate and reliable. They walk through a real case from a mid-sized fintech company that cut model deployment time from weeks to hours using CI/CD for ML. Along the way, they touch on monitoring drift, versioning data, and the cultural shift from research to engineering. If you've ever wondered why building a model is only half the battle, this episode gives you the other half. #DataScience #MLOps #MachineLearning #AIEngineering #ModelDeployment #FeatureStore #ModelRegistry #CICD #DataPipeline #ModelDrift #ProductionML #Fintech #Tech #BusinessPodcast #FexingoBusiness #Podcast #DataEngineering #DevOps Keep every episode free: buymeacoffee.com/fexingo","meta_description":"Episode 62 of The Data Science Podcast dives into the operational side of machine learning: MLOps. Lucas and Luna explore why so many models never make it…","key_points":[],"chapters":[],"topics":[],"duration_seconds":570,"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-mlops-to-keep-models-in-production/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-mlops-to-keep-models-in-production.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}