Skip to content

Latest commit

 

History

History
15 lines (12 loc) · 1.51 KB

README.md

File metadata and controls

15 lines (12 loc) · 1.51 KB
Raw

MNIST Handwritten Digit Recognition Using CNN

Python NumPy Jupyter TensorFlow Keras

The MNIST dataset is an acronym that stands for the Modified National Institute of Standards and Technology dataset.It is a dataset of 60,000 small square 28×28 pixel grayscale images of handwritten single digits between 0 and 9.The task is to classify a given image of a handwritten digit into one of 10 classes representing integer values from 0 to 9, inclusively. It can be simply imported from Keras Datasets using from keras.datasets import mnist

Steps to run the code

  • Run the Jupyter Notebook named as MNIST_DigitRecognition_UsingCNN.ipynb
  • Save the weight as mnist.h5
  • Using graphical user interface test the model -> Run gui.py

Result

Test loss: 0.0241182143806917
Test accuracy: 0.9933000206947327