This notebook demonstrates and allows you to play with the LeNet model.

The first cell loads the example in a new cell. Execute it.

Then, you can look at that example and run it to define the model.

Next, there is a cell that runs the model. It allows you to play with some of the hyper-parameters.

You can change the example code itself. You can reload the original code in a new cell by running the load cell again.

This example takes about 9m to execute on a GTX750 Ti with CuDNN v5.

To see the other files used by lenet.py run in a new cell: %load logistic_sgd.py or %load mlp.py.

Two possible changes you could try:

• change the non linearity of the convolution to a rectifier unit,
• add an extra mlp layer,
• limit the number of training epochs to iterate more rapidly on code change.