Deep Learning Illustrated, Part 2: How Does a Neural Network Learn?

Let’s say we want to create a neural network that predicts the daily revenue of ice cream sales using the features temperature and day of the week. This is the training dataset we’re using: <img alt="" src="https://miro.medium.com/v2/resize:fit:770/1*5fkl3uixCEFumzb4gSQ8AQ.png" style="height:430px; width:700px" /> To build a neural network, as we learned in the previous article, we need to first decide on its architecture. This includes determining the number of hidden layers, the number of neurons in each layer, and the activation function of each neuron. Let’s say we decided our architecture is: 1 hidden layer with 2 neurons, and 1 output neuron, all using the rectifier activation function. <a href="https://towardsdatascience.com/deep-learning-illustrated-part-2-how-does-a-neural-network-learn-481f70c1b474">Visit Now</a>