A Convolutional Neural Network model created using PyTorch library over the MNIST dataset to recognize handwritten digits .
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 is a widely used and deeply understood dataset and, for the most part, is “solved.” Top-performing models are deep learning convolutional neural networks that achieve a classification accuracy of above 99%, with an error rate between 0.4 %and 0.2% on the hold out test dataset.
- clone the repositiory or download it
- install the dependencies included in the requirement.txt file
- run python app.py command to start the flask server
- The server will start at http://127.0.0.1:5000 url
- Navigate to the url and try it out.