Machine Learning Model Concepts by Kumar Tipu (12 results)

Condition: New.

Condition: New. In English.

Condition: New.

Taschenbuch. Condition: Neu. Machine Learning Model Concepts: A Comprehensive Guide | Rupesh Kumar Tipu | Taschenbuch | 76 S. | Englisch | 2024 | LAP LAMBERT Academic Publishing | EAN 9786207805693 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. …

PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Condition: New. Print on Demand.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 76 pp. Englisch.

Condition: New. PRINT ON DEMAND.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book offers an in-depth exploration of the principles, techniques, and applications of machine learning. Starting with foundational concepts such as data preprocessing and model evaluation, the book covers both supervised learning models like regression and classification, and advanced topics like ensemble learning, neural networks, and deep learning. Practical considerations, including handling imbalanced data, feature engineering, and preventing data leakage, are thoroughly discussed to help build robust models. Designed for students, professionals, and enthusiasts alike, this guide provides valuable insights and practical knowledge to navigate and excel in the field of machine learning.…

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book offers an in-depth exploration of the principles, techniques, and applications of machine learning. Starting with foundational concepts such as data preprocessing and model evaluation, the book covers both supervised learning models like regression and classification, and advanced topics like ensemble learning, neural networks, and deep learning. Practical considerations, including handling imbalanced data, feature engineering, and preventing data leakage, are thoroughly discussed to help build robust models. Designed for students, professionals, and enthusiasts alike, this guide provides valuable insights and practical knowledge to navigate and excel in the field of machine learning.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 76 pp. Englisch.…