Dan Becker dansbecker

##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

	from sklearn.datasets import fetch_20newsgroups
	from sklearn.feature_extraction.text import TfidfVectorizer
	from sklearn.linear_model import LogisticRegression
	from sklearn.pipeline import Pipeline
	import pandas as pd
	import numpy as np

	# Grab just two categories from the 20 newsgroups dataset
	categories=['sci.space', 'rec.autos']

	from sklearn.datasets import fetch_20newsgroups
	from sklearn.feature_extraction.text import TfidfVectorizer

	from sklearn.linear_model import LogisticRegression
	# A pipeline "stitches together" the various steps of a modeling process into a single piece. You should either try to get a separate explanation of this, or try to do without it.
	# In general pipelines are pretty cool. But, one more thing to learn.
	from sklearn.pipeline import Pipeline
	import pandas as pd
	import numpy as np