🧠 TheSequence Quiz

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🧠 TheSequence Quiz

Welcome to The Sequence Quiz. Are you ready to test your knowledge after reading the current Edge#11? Be sure to be subscribed to TheSequence.ai if you haven't already: for the active participants we have a few surprises coming soon!

And now to the questions ➡️

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Meta-learning concept shows similarities with other machine learning ideas such as transfer learning or multi-task learning. What is the core difference? *

3 points

meta-learning main focus is to reuse knowledge learned in previous tasks

meta-learning enables knowledge reusability and the mechanics for generalizing learning methods and acquiring knowledge faster

meta-learning methods can perform on fewer datasets but spend more time acquiring knowledge as they go deeper into understanding it

Model-Agnostic Meta-Learning (MAML) is a technique proposed by researchers from Berkeley AI Research Lab. The core principle of MAML: *

3 points

a meta-learning method agnostic to the architecture of the target deep learning models

a meta-learning method that produces more efficient deep learning models

a meta-learning method that works with a larger set number of learning parameters to train a model on a new task

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