Аннотация
If you are looking for an engaging book, rich in learning features, which will guide you through the field of Machine Learning, this is it. This book is a modern, concise guide of the topic. It focuses on current ensemble and boosting methods, highlighting contemporray techniques such as XGBoost (2016), Shap (2017) and CatBoost (2018), which are considered novel and cutting edge models for dealing with supervised learning methods. The author goes beyond the simple bag-of-words schema in Natural Language Processing, and describes the modern embedding framework, starting from the Word2Vec, in details. Finally the volume is uniquely identified by the book-specific software egeaML, which is a good companion to implement the proposed Machine Learning methodologies in Python.
![Agile Testing: A Practical Guide for Testers and Agile Teams [calibre 2.56.0]](https://www.rulit.me/data/programs/images/agile-testing-a-practical-guide-for-testers-and-agile-teams_566869.jpg "Many of the designations used by manufacturers and sellers to distinguish their products are claimed as trademarks. Where those designations appear in this book, and the publisher was aware of a trademark claim, the designations have been printed with initial capital letters or in all capitals.
The...")
![Компьютер для индивидуального предпринимателя [Как вести учет быстро, легко и безошибочно]](https://www.rulit.me/data/programs/images/kompyuter-dlya-individualnogo-predprinimatelya-kak-vesti-uch_473032.jpg "Для каждого предпринимателя одним из ключевых вопросов является постановка и организация бухгалтерского учета. Это неудивительно: без отлаженной бухгалтерии в...")
Комментарии к книге "Applied machine learning with python"