Machine training with Python. Müller A., ​​Guido S.

Machine training has become an integral part of various commercial and research projects, but this area is not a prerogative of large companies with powerful analytical teams. Even if you are still a beginner in using Python, this book will introduce you to the practical ways to build machine learning systems. With all the variety of data available today, the use of machine learning is limited only by your imagination. You will study the stages necessary for creating a successful machine learning project using Python and Scikit-Learn library. The authors of this book, Andreas Müller and Sarah Guido, focused on the practical aspects of the use of machine learning algorithms, and not their mathematical justification. The reader has the skill of using the libraries Numpy and MatPlotlib will allow you to extract even more useful information from this book.

This book will help you:

to get acquainted with the fundamental concepts and the area of ​​use of machine learning tools;

understand the advantages and disadvantages of widely used machine learning algorithms;

To study the methods of loading data processed during machine learning, including various aspects of working with data;

to master the advanced methods of evaluating the model and subtle setting up parameters;

to study the principles of constructing conveyors To combine models into chains and encapsulation of the working flow;

to master the methods of working with text data;

get recommendations for improving the skills related to machine learning and the science of data.