Random Search
- Tests random parameter combinations efficiently.
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Stemming
- Reduces words to their root forms.
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Feature Engineering
- Combines or transforms data to improve model accuracy.
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Model Evaluation
- Compares metrics to decide which model performs best.
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Lemmatization
- Uses grammar rules to find the proper root word.
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Data Augmentation
- Creates more samples by rotating or modifying existing ones.
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Model Deployment
- Puts trained models into apps or websites.
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Bag of Words
- Represents text by word frequency.
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Dimensionality Reduction
- Reduces number of variables while keeping key info.
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