TY  - GEN
AU  - Dyar, Melinda Darby
AU  - Gunter, Mickey E.
AU  - Tasa, Dennis [ill.]
TI  - Mineralogy and optical mineralogy
SN  - 9780939950812
U1  - 006.31 
PY  - 2008///
CY  - Chantilly
PB  - Mineralogical Society of America
KW  - Deep learning -- Machine learning
KW  - Big data -- Statistical methods
KW  - R [Computer program language]
N2  - Deep learning is a class of machine learning algorithms that uses multiple layers to progressively extract higher-level features from the raw input. Deep-learning architectures such as deep neural networks, deep belief networks, recurrent neural networks, and convolutional neural networks have been applied to fields including computer vision, machine vision, speech recognition, natural language processing, audio recognition, social network filtering, machine translation, bioinformatics, drug design, medical image analysis, material inspection, and board game programs, where they have produced results comparable to and in some cases surpassing human expert performance. Deep learning is at the heart of artificial intelligence, and achievements and errors in the field are driving a great and constant interest
ER  -