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Waterfall methodology

As explained in Delivering Machine Learning Projects: From design to deployment

Waterfall is a sequential software development methodology in which requirements, design, implementation, testing, and acceptance proceed in ordered stages.

Waterfall organizes software delivery as a sequence: gather requirements, create a design, turn it into a work program, implement, test, and obtain user acceptance. section 1.3

Its structured sequence creates predictable handoffs but exposes important delivery risks:

  • Disconnecting users from implementation can produce software that does not meet real needs. section 1.3
  • Separating project managers from implementation makes complexity and cost harder to estimate accurately. section 1.3
  • Big requirements upfront became less attractive as project complexity and uncertainty increased. section 1.3

Later adaptations added feedback between stages, while Spiral and V-model approaches explored alternatives. Agile shifted emphasis toward working software, customer collaboration, and accepting change. section 1.3

How Delivering Machine Learning Projects: From design to deployment covers it

How deep it goes
Defines the delivery sequence and critiques estimation, user-disconnection, and upfront-requirements risks without detailing governance procedures.
Examples
Uses requirements, designs, work programs, code, tests, and user acceptance as sequential project artifacts.
What you can do after
Evaluate sequential delivery by identifying handoff, estimation, user-fit, and change-management risks.
How it connects
Contrasts waterfall with agile development, Spiral, iterative feedback, and V-model approaches.

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This explainer was generated by Manning's knowledge graph from the text of Delivering Machine Learning Projects: From design to deployment. The section links point to the parts of the book it draws on.