1. Stepping up to images
To close, you are going to apply your knowledge to a new and different dataset.
2. Recognizing handwritten digits
This is the MNIST dataset, which contains images of handwritten digits. This is a very popular dataset for getting started working with images. There is an image of each handwritten digit, and each image is composed of a 28 pixel by 28 pixel grid. The image is represented by showing how dark each pixel is. So, 0 would be as light as possible, and 255 is as dark as possible. I've flattened the 28 x 28 grid for you into a 784 x 1 array for each image. Each image shows a digit like 0, 1, 2, 3 4, all the way up to 9. Your model will predict which digit it is that was written. So you will create a deep learning model taking in those 784 features for each image as inputs, and predicting digits from among 10 possible values for the output. -
3. Let's practice!