Building-Neural-Network-From-scratch

Programming Language: Python Input: Drawing some points on a 2D grid for two classes, at least 6 points for each class, most of those points should be distinguishable as class 1 or class 2. The coordinates (x, y) will be my input (x1, x2), the class that the point belongs to will be either 0 or 1. The output class is what my neural network should learn to classify. Requirement: Building my own neural network using only python’s available built-in functions, without any libraries/imports except numpy. The neural network should contain at least 2 layers: 1 hidden, 1 output. Prediction: The neural network will do the predictions. I just have to threshold the value after using the activation function to get the prediction and compare the prediction with the original and get %.