{"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 Active Learning to Label Smarter","slug":"how-data-scientists-use-active-learning-to-label-smarter","published_at":"2026-06-14T08:12:21+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-active-learning-to-label-smarter","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-0050.mp3","audio_url":"https://audio.fexingo.com/business/the-data-science-podcast/episode-0050.mp3","summary":"In this milestone 50th episode, Lucas and Luna explore active learning — a machine learning paradigm where the model itself chooses which data points to label, dramatically reducing manual annotation costs. They break down the core idea using a concrete example: training a fraud detection model for a payment processor processing 10 million transactions per day. Lucas explains uncertainty sampling, query-by-committee, and the 'exploration vs. exploitation' trade-off. Luna raises the practical challenge of label noise and how to handle it. They also discuss when active learning fails — like when the unlabeled pool doesn't represent real-world distribution. The conversation ties back to the broader theme: getting more value from fewer labels, a critical skill for any data scientist working with limited annotation budgets. #ActiveLearning #MachineLearning #DataScience #UncertaintySampling #QueryByCommittee #FraudDetection #Labeling #Annotation #SemiSupervisedLearning #ExplorationVsExploitation #ModelTraining #DataEfficiency #MLStrategy #Technology #Podcast #FexingoBusiness #BusinessPodcast #DataSciencePodcast Keep every episode free: buymeacoffee.com/fexingo","meta_description":"In this milestone 50th episode, Lucas and Luna explore active learning — a machine learning paradigm where the model itself chooses which data points to l…","key_points":[],"chapters":[],"topics":[],"duration_seconds":606,"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-active-learning-to-label-smarter/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-active-learning-to-label-smarter.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}