10 Questions
Which type of models can be updated with just one data sample?
Neural network models
Which type of models require the entire dataset to be used before performing dimensionality reduction?
Collaborative filtering models
What is the purpose of continual learning?
To update models frequently
What is one of the challenges of continual learning?
Updating models too frequently
What is the 22 Algorithm Challenge?
A challenge specific to matrix-based and tree-based models
Which model can be updated with just one data sample?
Neural network model
What is the purpose of shadow development?
To test models in production
What is the technique used by the collaborative filtering model?
Dimensionality reduction
Which type of testing involves releasing new features to a small subset of users?
Canary Release
Which model requires the entire dataset to be used before performing dimensionality reduction?
Collaborative filtering model
Test your knowledge on the challenges and strategies of continual learning in machine learning models with this algorithm-focused quiz. Explore concepts like stateless retraining, test in production, A/B testing, and more. Sharpen your skills and learn how to tackle the complexities of updating and improving models over time.
Make Your Own Quizzes and Flashcards
Convert your notes into interactive study material.
Get started for free
