Zobacz książki o podobnej tematyce

Więcej informacji o Data Mining

• Dane szczegółowe
• Opis
• Ulubione w innej kategorii

Za ten zakup dostaniesz 165 punkty

Opis

Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches. Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research. Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projectsPresents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methodsIncludes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interfaceIncludes open-access online courses that introduce practical applications of the material in the book

Szczegóły książki

Kategoria Książki po angielsku Computing & information technology Databases Data mining

• Pełny tytuł: Data Mining
• Podtytuł: Practical Machine Learning Tools and Techniques
• Autor: Ian Witten, Eibe Frank, Mark Hall, Christopher Pal
• Język: Angielski
• Oprawa: Miękka
• Liczba stron: 654
• EAN: 9780128042915
• ISBN: 0128042915
• ID: 12496219
• Wydawca: Elsevier Science & Technology
• Waga: 1348 g
• Wymiary: 234 × 190 × 28 mm
• Data wydania: 15. February 2011

Ulubione w innej kategorii

---

---

---