Scikit Learn Mastery Hands on Machine by Kumar Tipu (6 results)

Taschenbuch. Condition: Neu. Neuware -'Scikit-Learn Mastery: Hands-On Machine Learning' is a comprehensive exploration of the Scikit-Learn library, offering a deep dive into machine learning techniques. The book covers everything from data preprocessing, model building, and evaluation, to advanced methods like ensemble learning and neural networks. It serves as a practical guide, providing readers with the tools to implement, evaluate, and optimize machine learning models efficiently. With step-by-step tutorials and real-world examples, this book is designed to equip professionals and enthusiasts with the skills to harness the power of machine learning in their projects.Books on Demand GmbH, Überseering 33, 22297 Hamburg 56 pp. Englisch.

Taschenbuch. Condition: Neu. Scikit-Learn Mastery: Hands-On Machine Learning | Rupesh Kumar Tipu | Taschenbuch | Englisch | 2024 | LAP LAMBERT Academic Publishing | EAN 9786207473489 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

paperback. Condition: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 56 pp. Englisch.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Scikit-Learn Mastery: Hands-On Machine Learning is a comprehensive exploration of the Scikit-Learn library, offering a deep dive into machine learning techniques. The book covers everything from data preprocessing, model building, and evaluation, to advan.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 'Scikit-Learn Mastery: Hands-On Machine Learning' is a comprehensive exploration of the Scikit-Learn library, offering a deep dive into machine learning techniques. The book covers everything from data preprocessing, model building, and evaluation, to advanced methods like ensemble learning and neural networks. It serves as a practical guide, providing readers with the tools to implement, evaluate, and optimize machine learning models efficiently. With step-by-step tutorials and real-world examples, this book is designed to equip professionals and enthusiasts with the skills to harness the power of machine learning in their projects.