Time Series Forecasting with Python and XGBoost: An Ultimate Guide from a Data Scientist, How to Master Time Series with Supervised Machine Learning Methods

by Dario Radečić

A pretty short and to-the-point book for anyone with basic Python programming knowledge and is interested in time series forecasting. No non-relevant points, zero waste of time, and all you need in just 50 pages! Learn how to master time series forecasting with supervised machine learning methods with a book that will tell you how to predict for multiple periods into the future. With this guide, you will see how easy it is to use the XGBoost algorithm to make time series forecasts. At the end of this book, you will have an entire class called XGBTimeSeries that accepts time series data, trains the model, and makes predictions─just like any other regression algorithm from Scikit-Learn does. » Who is this book for? Anyone with basic Python programming knowledge or knows the basics of time series forecasting can have this book to boost their time series forecasting skills. To make better use of this book, you will need to be a little familiar with machine learning algorithms. No expert knowledge required─every line of code is explained! » About the author Dario Radečić is a Data scientist from Croatia and a regular publisher on Medium/Towards Data Science with more than 6K followers. He is known for writing to-the-point and concise sentences on very complex topics. So that, he achieved to stick a broad topic such as Time Series Forecasting with Python and XGBoost into just 50 pages.

57 pages, Kindle Edition

Published October 3, 2020