<commit_before>Notch Examples
==============

 * `demo_xor` creates a multilayer peceptron and trains it to calculate
    XOR function (to classify two linearly inseparable sets)

 * `demo_iris` trains a multilayer perceptron to classify the iris flower
    dataset; the demo uses some optional Notch features:
    it reads data from a CSV file, applies one-hot encoding to labels,
    and applies softmax activation with cross-entropy loss on output

 * `demo_io` shows how to save and load a multilayer perceptron


How to build examples
---------------------

### On Linux

    mkdir build
    cd build
    cmake ..
    make


### On Windows

To build using GNU C++, install MinGW and CMake:

    mkdir build
    cd build
    cmake.exe -G "MinGW Makefiles" .`
    mingw32-make

For a debug build use

    cmake.exe -G "MinGW Makefiles" -DCMAKE_BUILD_TYPE=Debug ..

To build using Visual Studio 2013 (Community):
<commit_msg>udpate examples' README with descriptions of demo_mnist and demo_twospirals<commit_after>Examples
========

Notch examples can be founds in the `examples/` directory of the source
distribution:

 * `demo_xor` creates a multilayer peceptron and trains it to calculate
    XOR function (to classify two linearly inseparable sets).

 * `demo_iris` trains a multilayer perceptron to classify the iris flower
    dataset. The demo uses some optional Notch features:
    it reads data from a CSV file, applies one-hot encoding to labels,
    and applies softmax activation with cross-entropy loss on output.

 * `demo_mnist` trains a multilayer perceptron to classify hand-written
    digit images from the famous MNIST bechmark.

 * `demo_twospirals` trains a multilayer perceptron on a two-spiral
    classification problem. The problem is known to be difficult for
    neural networks. This example uses SQUARE dataset augmentation
    and ADADELTA training schedule to solve the problem.

 * `demo_io` shows how to save and load a multilayer perceptron.


How to build examples
---------------------

### On Linux

    mkdir build
    cd build
    cmake ..
    make


### On Windows

To build using GNU C++, install MinGW and CMake:

    mkdir build
    cd build
    cmake.exe -G "MinGW Makefiles" .`
    mingw32-make

For a debug build use

    cmake.exe -G "MinGW Makefiles" -DCMAKE_BUILD_TYPE=Debug ..

To build using Visual Studio 2013 (Community):

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