{"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 AutoML for Production Pipelines","slug":"how-data-scientists-use-automl-for-production-pipelines","published_at":"2026-07-18T20:47:18+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-automl-for-production-pipelines","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-0118.mp3","audio_url":"https://audio.fexingo.com/business/the-data-science-podcast/episode-0118.mp3","summary":"Episode 118 of The Data Science Podcast digs into the practical reality of AutoML in production—beyond the hype. Lucas and Luna walk through a real case: a mid-size e-commerce company that used AutoML to automate feature engineering and model selection for its real-time pricing engine. They break down the trade-offs between speed and interpretability, the hidden cost of compute, and why one data scientist's 'set it and forget it' experiment nearly broke the pipeline. Listeners will learn the concrete difference between AutoML as a productivity tool and AutoML as a black box, plus a simple heuristic for deciding when to automate and when to keep a human in the loop. #AutoML #MachineLearning #DataScience #MLOps #FeatureEngineering #ModelSelection #NeuralArchitectureSearch #AutomatedMachineLearning #ProductionML #RealTimePricing #ECommerce #Interpretability #DataPipeline #Technology #FexingoBusiness #BusinessPodcast #DataSciencePodcast #LucasAndLuna Keep every episode free: buymeacoffee.com/fexingo","meta_description":"Episode 118 of The Data Science Podcast digs into the practical reality of AutoML in production—beyond the hype. Lucas and Luna walk through a real case:…","key_points":[],"chapters":[],"topics":[],"duration_seconds":510,"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-automl-for-production-pipelines/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-automl-for-production-pipelines.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}