The ML Workflow: Data to Prediction
Learners will walk through the end-to-end pipeline from raw data collection and cleaning to model training, evaluation, and deployment.
The End-to-End ML Pipeline
Building ML is more than training a model — it's a full pipeline. Knowing all the stages keeps you from rushing straight to modelling too soon.
Stage 1: Define the Problem
Stage one is to define the problem: what are you predicting, why does it matter, and how will you measure success? Vague goals make vague models.