Exercise: Implement deep networks for digit classification
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=== Step 3: Train the softmax classifier on the L2 features === | === Step 3: Train the softmax classifier on the L2 features === | ||
| - | Next, continue to forward propagate the L1 features through the second autoencoder (using <tt>feedForwardAutoencoder.m</tt>) to obtain the L2 hidden unit activations. These activations are then used to train the softmax classifier. You | + | Next, continue to forward propagate the L1 features through the second autoencoder (using <tt>feedForwardAutoencoder.m</tt>) to obtain the L2 hidden unit activations. These activations are then used to train the softmax classifier. You can either use <tt>softmaxTrain.m</tt> or directly use <tt>softmaxCost.m</tt> that you completed in [[Exercise:Softmax Regression]] to complete this part of the assignment. |
=== Step 4: Implement fine-tuning === | === Step 4: Implement fine-tuning === | ||
