How Data Scientists Use AutoML for Production Pipelines
from The Data Science Podcast with Fexingo: Analytics, Machine Learning, and Data-Driven Conversations Hosted by Fexingo
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
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