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. We intend Fashion-MNIST to serve as a direct drop-in replacement for the original MNIST dataset for benchmarking machine learning algorithms. It shares the same image size and structure of training and testing splits.
y2mate.is.-.Fashion.mp4
Source: TensorFlow, Google Cloud Tech
Links:
Keras
Kaggle
TensorFlow
ZalandoResearch
Paperswithcode
The original MNIST dataset contains a lot of handwritten digits. Members of the AI/ML/Data Science community love this dataset and use it as a benchmark to validate their algorithms. In fact, MNIST is often the first dataset researchers try. "If it doesn't work on MNIST, it won't work at all", they said. "Well, if it does work on MNIST, it may still fail on others." - Zalando Research
Data: Fashion Mnist
Validation accurary: 90%
Training time: 1min 27s
Resources: Google Colab Standard GPU
Model Architecture: 2Cov, 2MaxPool, Flatten, 2Dense, Final output
