6. Glossary
Transfer learning
A method of reusing what has been learned on one problem as an aid to solving a slightly different one. This is commonly practiced with deep convolutional networks, by supplementing the lower layers of a pre-learned network with new layers, then performing learning iterations on a new learning base.
Supervised learning
A category of statistical learning whose aim is to empirically model an input-output relationship, based on pairs of examples (x
n
, y
n
) where x
n
is an input vector, and y
n
an associated output vector (called the desired output).
Characteristic; feature
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