My project is “Ainize Fashion MNIST”, and here is the frontend endpoint on Ainize: https://main-ainize-fashion-mnist-frontend-nelsen129.endpoint.ainize.ai/
This project will classify input images into one of ten categories based on the Fashion-MNIST dataset.
I have a blog post on Medium, and you can find the links to the Github repos of the code through that blog post
Let me know if you have any questions or comments!
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. The fashion MNIST dataset consists of 60,000 images for the training set and 10,000 images for the testing set** . Each image is a 28 x 28 size 192.168.l.254 grayscale image categorized into ten different classes. Each image has a label associated with it. There are, in total, ten labels available, and they are: T-shirt/top. It was created by “re-mixing” the samples from NIST’s original datasets. The creators felt that since NIST’s training dataset was taken from American Census Bureau employees, while the testing dataset was taken from American high school students, it was not well-suited for machine learning experiments.