Exercise: Implement deep networks for digit classification
From Ufldl
(→Step 0: Initialize constants and parameters) |
(→Step 1: Train the data on the first stacked autoencoder) |
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=== Step 1: Train the data on the first stacked autoencoder === | === Step 1: Train the data on the first stacked autoencoder === | ||
| - | Train the first autoencoder on the training images to obtain its parameters. This step is identical to the corresponding step in the sparse autoencoder and STL assignments, so | + | Train the first autoencoder on the training images to obtain its parameters. This step is identical to the corresponding step in the sparse autoencoder and STL assignments, complete this part of the code so as to learn a first layer of features using your <tt>sparseAutoencoderCost.m</tt> and minFunc. |
=== Step 2: Train the data on the second stacked autoencoder === | === Step 2: Train the data on the second stacked autoencoder === | ||
