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A fully-connected neural network in C++ for the recognition of the handwritten digits found in the MNIST dataset.

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Handwriting Recognition (MNIST) - AdvPT Project WS 2023 in C++

This project is a fully-connected neural network developed in C++ for the recognition of handwritten digits found in the MNIST dataset.

Project Structure

The project is structured as follows:

  • build.sh: This script contains all necessary code to prepare/build the executables for the project.
  • mnist.sh: This script triggers the training and testing of the neural network implementation.
  • src/: This directory contains the source code for the project, including image_loader.cpp and label_loader.cpp.

Building the Project

To build the project, run the build.sh script. This will create a build directory (if it doesn't exist), navigate into it, run cmake and make to build the project, and then compile the image_loader.cpp and label_loader.cpp files.

./build.sh

Running the Project

To run the project, execute the mnist.sh script. This will trigger the training and testing of the neural network implementation.

./mnist.sh <config path>

Additional Notes

  • The project uses C++20 standard.
  • The project is developed and tested in a Linux environment.
  • The project is developed using the CLion 2023.3.4 IDE.ry.

License

This project is licensed under the MIT License - see the LICENSE file for details.

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A fully-connected neural network in C++ for the recognition of the handwritten digits found in the MNIST dataset.

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