When ML/AI is brought into discussion you will most often hear about technologies like Convolutional Neural Networks, Auto Encoders, Deep Fakes, computer generated art and much more. And it’s quite fair that we are excited by these fantastic pieces of math, software design and human brilliance. There is however a much humbler component of the ML/AI flow without which the high-end algorithms would not be able to shine so bright. That component is called “Feature Engineering” and in this talk I’ll go over the basics of what it is, how it works and why it deserves a lot of credit and attention.