<p><span>Extensive treatment of the most up-to-date topics</span></p><p><span>Provides the theory and concepts behind popular and emerging methods</span></p><p><span>Range of topics drawn from Statistics, Computer Science, and Electrical Engineering</span></p>
Principles and Theory for Data Mining and Machine Learning
β Scribed by Bertrand Clarke, Ernest Fokoue, Hao Helen Zhang (auth.)
- Publisher
- Springer
- Year
- 2009
- Tongue
- English
- Leaves
- 786
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Subjects
Signal, Image and Speech Processing
π SIMILAR VOLUMES
official instructor's manual for "Principles and Theory for Data Mining and Machine Learning" (2010), obtained right through Springer.com the book is the holy book of the mathematical underpinnings of Machine Learning; you might have some struggles at the beginning, but it certainly pays back. Enjo
Introduction -- Learning and intelligence -- Machine learning basics -- Knowledge representation -- Learning as search -- Attribute quality matters -- Data preprocessing -- Constructive induction -- Symbolic learning -- Statistical learning -- Artificial neural networks -- Cluster analysis -- Learn