Applied Deep Learning Foundations for AI Practitioners
Lesson 1: The Machine Learning Workflow
Lesson Objectives
By the end of this lesson, students should be able to:
- Name the stages of a basic ML workflow.
- Explain why the target outcome must be clear.
- Separate the business question from the model task.
Lesson Content
A machine learning project is not "add AI and hope." It is a workflow. The usual stages are: define the problem, gather examples, choose labels or outcomes, train or configure the model, evaluate results, improve weak spots, and decide whether the system is safe enough to use.
The business question and the model task are related but not identical. "Improve customer support" is a business goal. "Classify incoming messages as billing, technical, account, or general" is a model task. Clear tasks are easier to train, test, and explain.
Before choosing tools, students should ask: What decision will improve? What data is available? What mistakes are costly? Who reviews the output?
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