# The Data Science Podcast with Fexingo: Analytics, Machine Learning, and Data-Driven Conversations

Page: https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831
Text version: https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831.md
RSS feed: https://feeds.fexingo.com/business/the-data-science-podcast.xml
Official site: https://www.fexingo.com/
Author: Fexingo
Episodes: 118

## Resource

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…

## Machine-readable

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## Episodes
- [How Data Scientists Use AutoML for Production Pipelines](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) — 2026-07-18T20:47:18+00:00
- [How Data Scientists Use Reservoir Computing for Time Series](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-reservoir-computing-for-time-series) — 2026-07-18T08:28:51+00:00
- [How Data Scientists Use Differential Privacy in Practice](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-differential-privacy-in-practice) — 2026-07-17T21:01:59+00:00
- [How Data Scientists Use Bayesian A-B Testing for Smarter Decisions](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-bayesian-a-b-testing-for-smarter-decisions) — 2026-07-17T08:38:54+00:00
- [How Data Scientists Use GraphRAG for Enterprise Knowledge Discovery](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-graphrag-for-enterprise-knowledge-discovery) — 2026-07-16T21:02:17+00:00
- [How Data Scientists Use Knowledge Graphs for Recommendation Systems](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-knowledge-graphs-for-recommendation-systems) — 2026-07-16T08:39:27+00:00
- [How Data Scientists Use Causal Inference for Business Decisions](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-causal-inference-for-business-decisions) — 2026-07-15T20:50:36+00:00
- [How Data Scientists Use Graph Neural Networks for Fraud Detection](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-graph-neural-networks-for-fraud-detection) — 2026-07-15T08:38:40+00:00
- [How Data Scientists Use Retrieval Augmented Generation for Enterprise Search](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-retrieval-augmented-generation-for-enterprise-search) — 2026-07-14T20:50:27+00:00
- [How Data Scientists Build Guardrails for Large Language Models](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-build-guardrails-for-large-language-models) — 2026-07-14T08:39:43+00:00
- [How Data Scientists Are Building AI Agents That Actually Work](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-are-building-ai-agents-that-actually-work) — 2026-07-13T21:15:20+00:00
- [How Data Scientists Use Data Version Control for Reproducibility](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-data-version-control-for-reproducibility) — 2026-07-13T08:53:45+00:00
- [How Data Scientists Use Feature Stores for Reproducible ML](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-feature-stores-for-reproducible-ml) — 2026-07-12T21:10:35+00:00
- [How Data Scientists Use Federated Learning for Privacy-Preserving ML](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-federated-learning-for-privacy-preserving-ml) — 2026-07-12T08:39:11+00:00
- [How Data Scientists Use Gradient Boosting for Tabular Data](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) — 2026-07-11T20:56:53+00:00
- [How Data Scientists Use Monte Carlo Simulations for Risk](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-monte-carlo-simulations-for-risk) — 2026-07-11T08:34:52+00:00
- [How Data Scientists Use SBERT for Semantic Search at Scale](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-sbert-for-semantic-search-at-scale) — 2026-07-10T21:06:17+00:00
- [How Data Scientists Build Interpretable ML Models with SHAP](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-build-interpretable-ml-models-with-shap) — 2026-07-10T08:58:30+00:00
- [How Data Scientists Use Synthetic Data for Model Training](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-synthetic-data-for-model-training-2) — 2026-07-09T21:03:26+00:00
- [How Data Scientists Use Temporal Fusion Transformers for Time Series Forecasting](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-temporal-fusion-transformers-for-time-series-forecasting) — 2026-07-09T08:40:15+00:00
- [How Spotify Uses Reinforcement Learning for Playlist Personalization](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-spotify-uses-reinforcement-learning-for-playlist-personalization) — 2026-07-08T20:57:00+00:00
- [Data Scientists Use Counterfactual Explanations for Model Debugging](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/data-scientists-use-counterfactual-explanations-for-model-debugging) — 2026-07-08T10:35:01+00:00
- [How Data Scientists Use Multimodal Models for Zero-Shot Learning](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-multimodal-models-for-zero-shot-learning) — 2026-07-07T21:00:43+00:00
- [How Data Scientists Use Nearest Neighbors for Anomaly Detection](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-nearest-neighbors-for-anomaly-detection) — 2026-07-07T08:49:58+00:00
- [Data Scientists Use Active Learning to Label Smarter](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/data-scientists-use-active-learning-to-label-smarter) — 2026-07-06T21:02:41+00:00
- [How Data Scientists Use MLOps to Keep Models in Production](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) — 2026-06-20T08:23:45+00:00
- [How Data Scientists Use Vector Databases for RAG Systems](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-vector-databases-for-rag-systems) — 2026-06-19T20:45:11+00:00
- [How Data Scientists Are Using Anomaly Detection in Real Time](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-are-using-anomaly-detection-in-real-time) — 2026-06-19T08:00:11+00:00
- [How Data Scientists Use Bayesian A-B Testing for Better Decisions](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-bayesian-a-b-testing-for-better-decisions) — 2026-06-18T20:24:03+00:00
- [How Data Scientists Use Synthetic Data for Model Training](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-synthetic-data-for-model-training) — 2026-06-18T08:15:43+00:00
- [How Data Scientists Estimate Causal Effects with Double Machine Learning](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-estimate-causal-effects-with-double-machine-learning) — 2026-06-17T20:19:44+00:00
- [How Data Scientists Use Transfer Learning to Solve Cold Start Problems](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-transfer-learning-to-solve-cold-start-problems) — 2026-06-17T08:17:13+00:00
- [How Data Scientists Use Knowledge Graphs to Connect Disparate Data](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-knowledge-graphs-to-connect-disparate-data) — 2026-06-16T20:16:10+00:00
- [How Data Scientists Use Causal Inference to Drive Business Decisions](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-causal-inference-to-drive-business-decisions) — 2026-06-16T08:11:10+00:00
- [How Data Scientists Use Federated Learning to Protect Privacy](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-federated-learning-to-protect-privacy) — 2026-06-15T20:34:23+00:00
- [How Data Scientists Use Reinforcement Learning for Dynamic Pricing](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-reinforcement-learning-for-dynamic-pricing) — 2026-06-15T08:20:53+00:00
- [How Data Scientists Build Churn Prediction Models That Actually Work](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-build-churn-prediction-models-that-actually-work) — 2026-06-14T20:20:35+00:00
- [How Data Scientists Use Active Learning to Label Smarter](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) — 2026-06-14T08:12:21+00:00
- [How Data Scientists Use Distributed Computing for Massive Datasets](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-distributed-computing-for-massive-datasets) — 2026-06-13T21:07:20+00:00
- [How Data Scientists Are Using TinyML on Edge Devices](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-are-using-tinyml-on-edge-devices) — 2026-06-13T08:05:36+00:00
- [How Data Scientists Use NLP to Detect Misinformation](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-nlp-to-detect-misinformation) — 2026-06-12T20:20:25+00:00
- [Data Scientists Are Using Graph Neural Networks for Fraud Detection](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/data-scientists-are-using-graph-neural-networks-for-fraud-detection) — 2026-06-12T10:53:56+00:00
- [How Data Scientists Use Counterfactual Explanations to Build Trust](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-counterfactual-explanations-to-build-trust) — 2026-06-11T20:28:46+00:00
- [How Data Scientists Use Shapley Values to Explain Model Predictions](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-shapley-values-to-explain-model-predictions) — 2026-06-11T08:17:35+00:00
- [How Data Science Is Changing the Way We Diagnose Disease](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-science-is-changing-the-way-we-diagnose-disease) — 2026-06-10T20:22:15+00:00
- [How Data Scientists Build Recommendation Engines from Scratch](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-build-recommendation-engines-from-scratch) — 2026-06-10T08:08:25+00:00
- [Why Data Science Projects Fail at the Deployment Stage](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/why-data-science-projects-fail-at-the-deployment-stage) — 2026-06-09T20:15:06+00:00
- [When Data Scientists Should Use Synthetic Control Methods](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/when-data-scientists-should-use-synthetic-control-methods) — 2026-06-09T08:15:19+00:00
- [How MLOps Teams Are Using Model Monitoring to Prevent Silent Failures](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) — 2026-06-08T20:10:05+00:00
- [How Data Scientists Use Bayesian A-B Testing](https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-bayesian-a-b-testing) — 2026-06-08T07:56:33+00:00

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