This project is Capstone project for the course "Getting started with tensorflow 2" offered by Imperial College London on Coursera. The project is about SVHN dataset. This is an image dataset of over 600,000 digit images in all, and is a harder dataset than MNIST as the numbers appear in the context of natural scene images. SVHN is obtained from house numbers in Google Street View images. In this notebook, I created a neural network that classifies real-world images digits. I used concepts from throughout this course in building, training, testing, validating and saving Tensor.