Graphical introduction to Machine Learning
Don’t be scared of math—it’s just numbers. And since every number can be plotted on a graph, we can think of machine learning as patterns and pictures and teaching the computer to recognize those pictures.
While that approach is simplistic, the truth is that nobody is smart enough to carry out all the math needed for machine learning. Even if you fully understood the theory behind it, it is impossible for the human brain to think in the many trillions (yes—trillions) of dimensions of data points used in some ML projects. And even if we got that far, the sheer volume of calculations needed would take longer than a human lifetime to work through.
Happily, the machine in machine learning means there are tools available to help us. There are prebuilt toolkits (libraries) available that we’ll use to train our models. And while it does help to understand the strengths of each toolkit, you can get a long way...