parrallel processing project

Example usage:

    // The dimensions of the neural network
    const int INPUT_SIZE = 4;
    const int HIDDEN_LAYER_1_SIZE = 12;
    const int HIDDEN_LAYER_2_SIZE = 6;
    const int OUTPUT_SIZE = 3;

    // Constructing the neural network
    auto *network = new NeuralNetwork();
    network->addNeuralLayer(INPUT_SIZE, HIDDEN_LAYER_1_SIZE, Activation::relu);
    network->addNeuralLayer(HIDDEN_LAYER_2_SIZE, Activation::relu);
    network->addNeuralLayer(OUTPUT_SIZE, Activation::softmax);

    // TODO: Load weights

    // Evaluating the neural network with a set of inputs
    auto *evaluationInput = new double[INPUT_SIZE] { 1.5, 1.2, 5.3, 7.3 };
    network->evaluate(evaluationInput);

mnist

the mnist dataset is sourced from https://pjreddie.com/projects/mnist-in-csv/ originally it was realeased in a binary format, but a nice lad transferred it to a csv file format to make it easy to read

• minstdriver.cpp : is a simple program that illustrates how reading in the images.

you can look at it yourself and understand it but I will outline the key ideas

follow these steps to use mnist

1. import header files

#include "ImageGrayscale8Bit.h"
#include "ImageIO.h"

2. read all images into a vector

the csv file can be downloaded from https://pjreddie.com/projects/mnist-in-csv/

    string infile = "mnist.csv"; //the path to the image csv file
    vector<ImageGrayscale8Bit> images = ImageIO::readMINSTCSV(infile);

3. Do what you need to with the images

here are some of the methods that will be useful for ImageGrayscale8Bit

    //properties
    int getWidth() const;
    int getHeight() const;
    int size() const;

    //pixel getters
    unsigned char getIntensity(int x, int y) const;
    unsigned char getIntensity(int index) const;