Session 3 of the “Machine Learning for Industry 4.0” workshop series by the Department of Computer and Data Science, dove deep into building a model training pipeline to select the best-performing model for a US case study. Once the models were developed, the participants used a variety of metrics to measure their performance, ensuring the most optimal solution was identified.

During the session, FastAPI and backend development were introduced, setting the stage to deploy the machine learning model into production. This week was packed with invaluable insights, preparing participants to bridge the gap between development and real-world application.