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Machine Learning Academy · Lesson

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.

All lessons in this course

  1. Traditional Programming vs Machine Learning
  2. Supervised, Unsupervised, and Reinforcement Learning
  3. The ML Workflow: Data to Prediction
  4. ML in the Real World: Use Cases and Limitations
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