Mohlo by se vám také líbit

Více informací o knize Machine Learning: From Theory to Applications

• Parametry knihy
• Anotace
• Oblíbené z jiného soudku

Nákupem získáte 168 bodů

Anotace knihy

This volume includes some of the key research papers in the area of machine learning produced at MIT and Siemens during a three-year joint research effort. It includes papers on many different styles of machine learning, organized into three parts. Part I, theory, includes three papers on theoretical aspects of machine learning. The first two use the theory of computational complexity to derive some fundamental limits on what is efficiently learnable. The third provides an efficient algorithm for identifying finite automata. Part II, artificial intelligence and symbolic learning methods, includes five papers giving an overview of the state of the art and future developments in the field of machine learning, a subfield of artificial intelligence dealing with automated knowledge acquisition and knowledge revision.Part III, neural and collective computation, includes fivepapers sampling the theoretical diversity and trends in the vigorous new research field of neural networks: massively parallel symbolic induction, task decomposition through competition, phoneme discrimination, behavior-based learning, and self-repairing neural networks.

Parametry knihy

Zařazení knihy Knihy v angličtině Computing & information technology Computer science Artificial intelligence

• Plný název: Machine Learning: From Theory to Applications
• Podnázev: Cooperative Research at Siemens and MIT
• Autor: Stephen J. Hanson, Werner Remmele, Ronald L. Rivest
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 276
• EAN: 9783540564836
• ISBN: 3540564837
• ID: 01565618
• Nakladatelství: Springer, Berlin
• Hmotnost: 383 g
• Rozměry: 233 × 155 × 15 mm
• Rok vydání: 1993

Oblíbené z jiného soudku

---

---

---