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# Introduction
The present session will introduce the Python classes and how to create your own Artificial Neural Network (ANN) class. The class will implement the `__init__`, `feedforward`, and `backpropagation` methods.
Each method will be described in detail to understand the ANN’s inner work. Then, the handwriting MNIST dataset will be used to train and test our ANN.
# Objectives
- Learn the basics of using Python Classes
- Create methods for: create, feedforward, and backpropagation
- Train the ANN
- Test the ANN
# Pending tasks (Your work)
- Create a Python function to evaluate the ANN’s performance by passing all the test images(`mnist_test.csv`) and compare the target with the ANN’s results.
- Make a plot of the ANN’s evolution performance for at least 10 combinations of the number of hidden nodes, learning rate, and the number of epochs.