The MNIST handwritten digit classification problem is a standard dataset used in computer vision and deep learning.
- Learn about the MNIST handwritten digits dataset
- Use the Keras API to load the MNIST dataset and prepare it for training
- Create a simple neural network to perform image classification
- Train the neural network using the prepped MNIST dataset
- Observe the performance of the trained neural network
In the history of deep learning, the accurate image classification of the MNIST dataset, a collection of 70,000 grayscale images of handwritten digits from 0 to 9, was a major development. While today the problem is considered trivial, doing image classification with MNIST has become a kind of "Hello World" for deep learning.