R. Nicolas Scala for Machine Learning

Leverage Scala and Machine Learning to construct and study systems that can learn from data
1. Auflage 2014
ISBN: 978-1-78355-875-9
Verlag: De Gruyter
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 520 Seiten

No detailed description available for "Scala for Machine Learning".

Autoren/Hrsg.

R. Nicolas, Patrick

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Mensch-Maschine-Interaktion Informationsarchitektur
• Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Algorithmen & Datenstrukturen
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Datenbankdesign & Datenbanktheorie

Inhaltsverzeichnis

Table of Contents - Getting Started
- Hello World
- Data preprocessing
- Unsupervised Learning
- Naïve Bayes Classifiers
- Regression and Regularization
- Sequential Data Models HMM and CRF
- Kernel models and Support Vector Machines
- Artificial Neural Networks
- Genetic Algorithms
- Reinforcement learning
- Scalable Frameworks
- Appendix: Appendix
- Appendix B

Über Autor(innen)

R. Nicolas Patrick:
Patrick R. Nicolas is the director of engineering at Agile SDE, California. He has more than 25 years of experience in software engineering and building applications in C++, Java, and more recently in Scala/Spark, and has held several managerial positions. His interests include real-time analytics, modeling, and the development of nonlinear models.