A Review of Deep Machine Learning
| Autor: | Yong Zhao Zhan, Frank Banaseka Kataka, Benjamin Ghansah, Dickson Keddy Wornyo, Ben-Bright Benuwa |
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| Rok vydání: | 2016 |
| Předmět: |
Learning classifier system
Computer science Active learning (machine learning) business.industry 020209 energy Algorithmic learning theory 02 engineering and technology Machine learning computer.software_genre Robot learning Computational learning theory 0202 electrical engineering electronic engineering information engineering Unsupervised learning 020201 artificial intelligence & image processing Instance-based learning Artificial intelligence Hyper-heuristic business computer |
| Zdroj: | International Journal of Engineering Research in Africa. 24:124-136 |
| ISSN: | 1663-4144 |
| DOI: | 10.4028/www.scientific.net/jera.24.124 |
| Popis: | The rapid increase of information and accessibility in recent years has activated a paradigm shift in algorithm design for artificial intelligence. Recently, deep learning (a surrogate of Machine Learning) have won several contests in pattern recognition and machine learning. This review comprehensively summarises relevant studies, much of it from prior state-of-the-art techniques. This paper also discusses the motivations and principles regarding learning algorithms for deep architectures. |
| Databáze: | OpenAIRE |
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