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Synopsis
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.
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About the Author
Andrea Giussani is an Academic Fellow in Computer Science at Bocconi University. He holds a PhD in Statistics, and he has published in several peer-reviewed journals.
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Applied Machine Learning With Python
Published by
, Bocconi Univ Pr 2020-03-30, 2020
ISBN 10: 8831322044
ISBN 13: 9788831322041
Used
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Seller: Usatopoli libriusatierari, Brugherio, MB, Italy
Seller rating 5 out of 5 stars
brossura. Condition: Molto buono (Very Good). 1 ED 2020 IN OTTIME CONDIZIONI!rarissime evidenziatureENGLISH 8831322044 Molto buono (Very Good) . Book. Seller Inventory # bc_21471
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