Digging into the core of machine learning

After discussing the categorization of machine learning algorithms, we are going to dig into the core of machine learning—generalizing with data, and different levels of generalization, as well as the approaches to attain the right level of generalization.

Generalizing with data

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 challenge stems 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 zeros. 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...