The good thing about data is that there's a lot of it in the world. The bad thing is that it's hard to process this data. The challenges stem from the diversity and noisiness of the data. We humans usually process data coming into our ears and eyes. These inputs are transformed into electrical or chemical signals. On a very basic level, computers and robots also work with electrical signals. These electrical signals are then translated into ones and zeroes. However, we program in Python in this book and, on that level, normally we represent the data either as numbers, images, or texts. Actually, images and text aren't very convenient, so we need to transform images and text into numerical values.
Especially in the context of supervised learning, we have a scenario similar to studying for an exam. We have a...
