  This text aims to present and explain quantum machine learning algorithms to
a data scientist in an accessible and consistent way. The algorithms and
equations presented are not written in rigorous mathematical fashion, instead,
the pressure is put on examples and step by step explanation of difficult
topics. This contribution gives an overview of selected quantum machine
learning algorithms, however there is also a method of scores extraction for
quantum PCA algorithm proposed as well as a new cost function in feed-forward
quantum neural networks is introduced. The text is divided into four parts: the
first part explains the basic quantum theory, then quantum computation and
quantum computer architecture are explained in section two. The third part
presents quantum algorithms which will be used as subroutines in quantum
machine learning algorithms. Finally, the fourth section describes quantum
machine learning algorithms with the use of knowledge accumulated in previous
parts.
