# from scratch

Tensorflow insights - part 1: Image classification from zero to a trained model

When we start a machine learning project, the first mandatory question is where we get data from and how the data is prepared. Only when this stage has been completed, does we can go to the training stage. In this tutorial, we first introduce you how to use and prepare the [Stanford Dogs dataset](http://vision.stanford.edu/aditya86/ImageNetDogs/); then we show the 5 core steps to implement a neural network for training in Tensorflow. _You can reach the code version of this post in [here](https://github.com/willogy-team/insights--tensorflow/tree/main/part1)._