Fashion-MNIST Solver - Deep Learning from Scratch

• This project implements a neural network in C++ without the use of advanced libraries or frameworks.
• The neural net solves the Fashion-MNIST dataset using a backpropagation algorithm.

Compile & Run

• The project contains a runnable script called run.sh, which compiles and executes the code (and exports the results).
• The executable outputs two files to the root project directory:
  • train_predictions.csv - network predictions for the train set.
  • test_predictions.csv - network predictions for the test set.
  • Format:
    • One prediction per line.
    • Prediction for i-th input vector (ordered by the input .csv file) is on the i-th line in the associated output file.
    • Each prediction is a single integer 0 - 9.

Data Set

Fashion MNIST (https://arxiv.org/pdf/1708.07747.pdf) - a modern version of a well-known MNIST (http://yann.lecun.com/exdb/mnist/). It is a dataset of Zalando's article images ‒ consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image, associated with a label from 10 classes. The dataset is in CSV format. There are four data files included:

• fashion_mnist_train_vectors.csv - training input vectors
• fashion_mnist_test_vectors.csv - testing input vectors
• fashion_mnist_train_labels.csv - training labels
• fashion_mnist_test_labels.csv - testing labels