Deep Learning CNN for Fashion-MNIST Clothing Classification
Last Updated on August 28, 2020
The Fashion-MNIST clothing classification problem is a new standard dataset used in computer vision and deep learning.
Although the dataset is relatively simple, it can be used as the basis for learning and practicing how to develop, evaluate, and use deep convolutional neural networks for image classification from scratch. This includes how to develop a robust test harness for estimating the performance of the model, how to explore improvements to the model, and how to save the model and later load it to make predictions on new data.
In this tutorial, you will discover how to develop a convolutional neural network for clothing classification from scratch.
After completing this tutorial, you will know:
- How to develop a test harness to develop a robust evaluation of a model and establish a baseline of performance for a classification task.
- How to explore extensions to a baseline model to improve learning and model capacity.
- How to develop a finalized model, evaluate the performance of the final model, and use it to make predictions on new images.
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