Machine Learning in Python NumPy: Neural Network in 9 Steps

#artificialintelligence 

Although there are many clean datasets available online, we will generate our own for simplicity -- for inputs a and b, we have outputs a b, a-b, and a-b . Our dataset is split into training (70%) and testing (30%) set. Only training set is leveraged for tuning neural networks. Testing set is used only for performance evaluation when the training is complete. Data in the training set is standardized so that the distribution for each standardized feature is zero-mean and unit-variance.