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.
![Low-Level Programming [C, Assembly, and Program Execution on Intel® 64 Architecture]](https://www.rulit.me/data/programs/images/low-level-programming-c-assembly-and-program-execution-on-in_607209.jpg "This book aims to help you develop a consistent vision of the domain of low-level programming. We want to enable a careful reader to • Freely write in assembly language.
• Understand the Intel 64 programming model.
• Write maintainable and robust code in C11.
• Understand the compilation...")
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