{"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 Gradient Boosting for Tabular Data","slug":"how-data-scientists-use-gradient-boosting-for-tabular-data","published_at":"2026-07-11T20:56:53+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-gradient-boosting-for-tabular-data","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-0104.mp3","audio_url":"https://audio.fexingo.com/business/the-data-science-podcast/episode-0104.mp3","summary":"A deep dive into the enduring power of gradient boosting machines (GBMs) for structured, tabular data—the bread and butter of most real-world data science. Lucas and Luna explore why gradient boosting consistently wins Kaggle competitions and beats deep learning on many business problems. They break down the core mechanics: sequential tree-building, learning rate, and regularization. The episode focuses on a case study from a mid-size e-commerce company that used XGBoost to reduce customer churn prediction error by 18% year-over-year. They also discuss modern variants like LightGBM and CatBoost, and when to choose each. Practical guidance on hyperparameter tuning and common pitfalls (overfitting, categorical encoding) grounds the conversation in daily data-science work. Listeners will walk away understanding why gradient boosting remains a must-have in any data scientist's toolkit, especially for data with mixed data types and missing values. #GradientBoosting #XGBoost #LightGBM #CatBoost #TabularData #MachineLearning #DataScience #Kaggle #HyperparameterTuning #ChurnPrediction #EnsembleMethods #DecisionTrees #Regularization #FeatureEngineering #BusinessAnalytics #Technology #FexingoBusiness #BusinessPodcast Keep every episode free: buymeacoffee.com/fexingo","meta_description":"A deep dive into the enduring power of gradient boosting machines (GBMs) for structured, tabular data—the bread and butter of most real-world data science…","key_points":[],"chapters":[],"topics":[],"duration_seconds":551,"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-gradient-boosting-for-tabular-data/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-gradient-boosting-for-tabular-data.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}