an activation function is to introduce nonlinearities into the data and this is actually really important in real life because in real life almost all of our data is nonlinear and here's a concrete example if I told you to separate the green points from the red points using a linear function could you do that I don't think so right so you'd get something like this oh you could do it you wouldn't do very good job at it and no matter how deep or how large your network is if you're using a linear activation function you're just