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Natural language processing: a practical guide collection

Explore natural language processing through four focused guides for Canadian readers. Start with a defined question, examine the method and keep its limitations visible.

Natural language processing learning and planning

Start with the language

Define which languages, writing styles and domains the application must handle. Evaluate each separately before combining results into an overall score.

Prepare representative examples

Review labels, spelling variation and the mix of languages in a message. Keep related records together when splitting data so the test set remains informative.

Measure useful behaviour

Compare a simple baseline, inspect errors and decide which uncertain outputs should be reviewed by a person. A fluent response is not evidence that it is correct.

Keep the workflow accountable

Document how data is collected and retained, who can access it and what happens when the model cannot help. Use fictional or suitable public examples for learning.

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