Algorithm-Overview.md

# Algorithms

In the following chapters we treat the actual core of this book: The Machine Learning Algorithms.

We will see that there are several different methods for different applications. For each algorithm explained, there is a jupyter notebook which gives an example on how this method is used and how you can use it yourself in python with Scikit-Learn or the Keras and Tensorflow libraries.

The models themselves are separated into two different categories. 

First we will look at the mathematical models which are mostly used for classification and regression and function on a statistical method.

Second we will introduce neural networks which are models loosely based on the interactions of neurons in the human brain. Neural networks and deep learning are probably some of the most exciting fields of computer science in our time.

Every one of these algorithms have different methods to analyse data and are therefore used in different ways. Here is a good overview on how to approach the problem of choosing the right algorithm.

![Map Overview](./Overview-Map.png)

Source: <https://scikit-learn.org/stable/_static/ml_map.png>

*Written by Felix Matthias Krumm*