MLOps 101: Scoping, Latency, Data Curation, and Continuous Model Retraining - ML 143

Ben and Michael dive into the world of machine learning operations (MLOps) and discuss the complexities of building a computer vision pipeline to detect fishing boats at ports. They unpack the intricacies of MLOps basics and the challenges of implementing an effective computer vision model for traffic optimization and data collection at ports. From discussing the importance of exploratory data analysis (EDA) and data cleaning for image classification to the intricacies of continuous integration and deployment, this episode provides invaluable insights into the practical application of machine learning in real-world scenarios.SponsorsChuck's Resume TemplateDeveloper Book ClubBecome a Top 1% Dev with a Top End Devs MembershipAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacyBecome a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.