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What is eager learning or lazy learning?

Eager learning is when a model does all its computation before needing to make a prediction for unseen data. For example, Neural Networks are eager models.

Lazy learning is when a model doesn't require any training, but all of its computation during inference. An example of such a model is k-NN. Eager learning is also known as instance-based learning [1, 2, 3].

How does eager and lazy learning help me build a neural network system? And how can I use it for any target function?

To answer your second question, you can't employ lazy learning to train a neural network, because they are inherently eager models.

What is eager learning or lazy learning?

Eager learning is when a model does all its computation before needing to make a prediction for unseen data. For example, Neural Networks are eager models.

Lazy learning is when a model doesn't require any training, but all of its computation during inference. An example of such a model is k-NN. Lazy learning is also known as instance-based learning [1, 2, 3].

How does eager and lazy learning help me build a neural network system? And how can I use it for any target function?

To answer your second question, you can't employ lazy learning to train a neural network, because they are inherently eager models.

What is eager learning or lazy learning?

Eager learning is when a model does all its computation before needing to make a prediction for unseen data. For example, Neural Networks are eager models.

Lazy learning is when a model doesn't require any training, but all of its computation during inference. An example of such a model is k-NN. Eager learning is also known as instance-based learning [1, 2].

How does eager and lazy learning help me build a neural network system? And how can I use it for any target function?

To answer your second question, you can't employ lazy learning to train a neural network, because they are inherently eager models.

What is eager learning or lazy learning?

Eager learning is when a model does all its computation before needing to make a prediction for unseen data. For example, Neural Networks are eager models.

Lazy learning is when a model doesn't require any training, but all of its computation during inference. An example of such a model is k-NN. Eager learning is also known as instance-based learning [1, 2, 3].

How does eager and lazy learning help me build a neural network system? And how can I use it for any target function?

To answer your second question, you can't employ lazy learning to train a neural network, because they are inherently eager models.

What is eager learning or lazy learning?

Eager learning is when a model does all its computation before needing to make a prediction for unseen data. For example, Neural Networks are eager models. You can also check out the wikipedia page on eager learning (although it's quite poor).

Lazy learning is when a model doesn't require any training, but all of its computation during inference. An example of such a model is k-NN.

References:

1. wikipedia

2. Lazy Learning, DW Aha, 2013

Other sources: 1, 2, 3

How is a eager learning or lazy learning help me build a neural network system? And how can I use it for any target function?

To answer your secondary question, you can't employ lazy learning to train a neural network, because they are inherently eager models.

What is eager learning or lazy learning?

Eager learning is when a model does all its computation before needing to make a prediction for unseen data. For example, Neural Networks are eager models.

Lazy learning is when a model doesn't require any training, but all of its computation during inference. An example of such a model is k-NN. Eager learning is also known as instance-based learning [1, 2].

How does eager and lazy learning help me build a neural network system? And how can I use it for any target function?

To answer your second question, you can't employ lazy learning to train a neural network, because they are inherently eager models.