5 Reasons "Logistic Regression" should be the first thing you learn when becoming a Data Scientist

For me, studying Logistic regression first helped a lot when I started to learn Neural Networks. You can think of each neuron in the network as a Logistic Regression, it has the input, the weights, the bias you do a dot product to all of that, then apply some non linear function. Moreover, the final layer of a neural network is a simple linear model (most of the time). Let's look closer at the "output layer", you can see that this is a simple linear (or logistic) regression, we have the input (hidden layer 2), we have the weighs, we do a dot product and then add a non linear function (depends on the task). The first part (on the left) is trying to learn a good representation of the data that will help the second part (on the right) to perform a linear classification/regression.