This project aims to test different configurations for the Multilayer Perceptron using 3 datasets: MNIST, F-MNIST and K-MNIST.
- MNIST : database of handwritten digits;
- F-MNIST : Fashion-MNIST 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;
- K-MNIST: Kuzushiji-MNIST is a drop-in replacement for the MNIST dataset (28x28 grayscale, 70,000 images), provided in the original MNIST format as well as a NumPy format;
The visualization is also compiled into a streamlit script. To do this, just install the dependencies in requirements-streamlit.txt and run the following command:
streamlit run mlp_app.py