### Basic Three Layer Neural Network in Python

Introduction
As part of understanding neural networks I was reading Make Your Own Neural Network by Tariq Rashid. The book itself can be painful to work through, as it is written for a novice, not just in algorithms and data analysis, but also in programming. Although the code is a verbatim transcription from the text (see Source section), I published it to better understand how neural networks are designed, made easy by the use of a Jupyter Notebook, not to present this as my own work, although I do hope that this helps others develop their talents with data analytics.

Overview The code itself develops as follows:

Constructor set number of nodes in each input, hidden, output layer link weight matrices, wih and who weights inside the arrays are w_i_j, where link is from node i to node j in the next layer set learning rate activation function is the sigmoid function Define the Training Function convert inputs list to 2d array calculate signals into hidden layer calculate…

Overview The code itself develops as follows:

Constructor set number of nodes in each input, hidden, output layer link weight matrices, wih and who weights inside the arrays are w_i_j, where link is from node i to node j in the next layer set learning rate activation function is the sigmoid function Define the Training Function convert inputs list to 2d array calculate signals into hidden layer calculate…