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Questions and Answers
Which type of models can be updated with just one data sample?
Which type of models can be updated with just one data sample?
- Tree-based models
- Neural network models (correct)
- Collaborative filtering models
- Matrix-based models
Which type of models require the entire dataset to be used before performing dimensionality reduction?
Which type of models require the entire dataset to be used before performing dimensionality reduction?
- Matrix-based models
- Neural network models
- Tree-based models
- Collaborative filtering models (correct)
What is the purpose of continual learning?
What is the purpose of continual learning?
- To perform A/B testing
- To build user-item matrices
- To reduce the dimensionality of the dataset
- To update models frequently (correct)
What is one of the challenges of continual learning?
What is one of the challenges of continual learning?
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What is the 22 Algorithm Challenge?
What is the 22 Algorithm Challenge?
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Which model can be updated with just one data sample?
Which model can be updated with just one data sample?
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What is the purpose of shadow development?
What is the purpose of shadow development?
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What is the technique used by the collaborative filtering model?
What is the technique used by the collaborative filtering model?
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Which type of testing involves releasing new features to a small subset of users?
Which type of testing involves releasing new features to a small subset of users?
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Which model requires the entire dataset to be used before performing dimensionality reduction?
Which model requires the entire dataset to be used before performing dimensionality reduction?
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