##VGG16 model for Keras
This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.
It has been obtained by directly converting the Caffe model provived by the authors.
Details about the network architecture can be found in the following arXiv paper:
Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan, A. Zisserman
| /* | |
| This example uses Scala. Please see the MLlib documentation for a Java example. | |
| Try running this code in the Spark shell. It may produce different topics each time (since LDA includes some randomization), but it should give topics similar to those listed above. | |
| This example is paired with a blog post on LDA in Spark: http://databricks.com/blog | |
| Spark: http://spark.apache.org/ | |
| */ | |
| import scala.collection.mutable |
| import nltk | |
| text = """The Buddha, the Godhead, resides quite as comfortably in the circuits of a digital | |
| computer or the gears of a cycle transmission as he does at the top of a mountain | |
| or in the petals of a flower. To think otherwise is to demean the Buddha...which is | |
| to demean oneself.""" | |
| # Used when tokenizing words | |
| sentence_re = r'''(?x) # set flag to allow verbose regexps | |
| ([A-Z])(\.[A-Z])+\.? # abbreviations, e.g. U.S.A. |