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MNIST Classifier in C

Introduction

This project is a simple digit classifier for the MNIST dataset implemented in C. The primary goal is to revisit and reinforce the understanding of the backpropagation algorithm by implementing a neural network from scratch. In doing so I had to make a c matrix library, which I used as an opportunity to learn about optimized multithreaded matrix algorithms, utilizing either openMP, pthreads, or CUDA.

Key Objectives

  • Relearn and implement the backpropagation algorithm for neural network training.
  • Develop a modular and efficient C matrix library to support matrix operations.
  • Lay the groundwork for potential future enhancements, such as multithreaded matrix algorithms.

I followed this textbook, http://neuralnetworksanddeeplearning.com, which had very good information regarding the algorithms for the implementation.

Results

In the below output, I ran the program and got 95% accuracy on the mnist dataset

cc main.c -o net.exe -lm -g -Wall -pedantic
./net.exe
Starting epoch: 0
77.98 % correct, 7798/10000
.....
Starting epoch: 9
95.73 % correct, 9573/10000
Press q to exit, press any character to see the next evaluation

  ▓▩░░▓
  ██████▩▩▩▩▩▩▩▩░▓
  ▓▒▓▒░██████████░
        ▓ ▓▓▓▓ ██▒
              ▓█▩
              ██▓
             ░██▓
            ▓██▓
            ░█▩
            ▩█▓
           ▒█▩
          ▓██▓
          ██░
         ▩██
         ██▓
        ██▒
       ░██▓
      ▓███▓
      ▒███
      ▒█▩

returned 7 with value of 0.99, true value is 7

Conclusion

The conclusion I gained from all of this is to use BLAS and python as they greatly simplify and expediate the process. However I am thankful I learned lots regarding backproagation, and multithreaded matrix multiplication algorithms.