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Related: Deep Learning • Big dataMachine Learning is Fun! Part 3: Deep Learning and Convolutional Neural Networks Recognizing Objects with Deep Learning You might have seen this famous xkcd comic before. The goof is based on the idea that any 3-year-old child can recognize a photo of a bird, but figuring out how to make a computer recognize objects has puzzled the very best computer scientists for over 50 years. In the last few years, we’ve finally found a good approach to object recognition using deep convolutional neural networks. Large Network Dataset Collection Social networks Networks with ground-truth communities Communication networks Citation networks Collaboration networks
Finding Data on the Internet Skip to Content A Community Site for R – Sponsored by Revolution Analytics Home » How to » Finding Data on the Internet Finding Data on the Internet By RevoJoe on October 6, 2011 Installation - TFLearn Tensorflow Installation TFLearn requires Tensorflow (version >= 0.9.0) to be installed. Select the correct binary to install, according to your system: # Ubuntu/Linux 64-bit, CPU only, Python 2.7 $ export TF_BINARY_URL= # Ubuntu/Linux 64-bit, GPU enabled, Python 2.7# Requires CUDA toolkit 7.5 and CuDNN v5. For other versions, see "Install from sources" below. $ export TF_BINARY_URL= # Mac OS X, CPU only, Python 2.7: $ export TF_BINARY_URL= # Mac OS X, GPU enabled, Python 2.7: $ export TF_BINARY_URL= # Ubuntu/Linux 64-bit, CPU only, Python 3.4 $ export TF_BINARY_URL= # Ubuntu/Linux 64-bit, GPU enabled, Python 3.4# Requires CUDA toolkit 7.5 and CuDNN v5. For other versions, see "Install from sources" below. $ export TF_BINARY_URL= # Ubuntu/Linux 64-bit, CPU only, Python 3.5 $ export TF_BINARY_URL= # Ubuntu/Linux 64-bit, GPU enabled, Python 3.5# Requires CUDA toolkit 7.5 and CuDNN v5.
50 Resources for Getting the Most Out of Google Analytics Google Analytics is a very useful free tool for tracking site statistics. For most users, however, it never becomes more than just a pretty interface with interesting graphs. The resources below will help anyone, from the beginner to those who have been using Google Analytics for some time, learn how to get the most out of this great tool.
Data Sets The Pew Research Center's Internet Project is pleased to offer scholars access to raw data sets from our research. All uses of this data should reference the Pew Research Center as the source of the data and acknowledge that the Pew Research bears no responsibility for interpretations presented or conclusions reached based on analysis of the data. Our data sets are made available as single compressed archive files (.zip file). Download and Setup You can install TensorFlow either from our provided binary packages or from the github source. Requirements The TensorFlow Python API supports Python 2.7 and Python 3.3+. The GPU version works best with Cuda Toolkit 8.0 and cuDNN v5.1.
Common Google Universal Analytics Mistakes that kill your Analysis & Conversions I have audited hundreds of web analytics accounts and profiles. And each account/view had at least one or two issues which seriously stood in my way of getting optimum results from my analysis. I have put all of these issues into five broad categories: French National Election Study, 1995 Principal Investigator(s): Lewis-Beck, Michael S.; Mayer, Nonna; Boy, Daniel, et al. This national survey was conducted to study the attitudes and opinions of the French electorate during election year 1995. Information is provided on respondents' interest in politics, ideological leanings, voting behavior, party choice in the 1994 European elections, choice of presidential candidate in the first and second ballot of the 1995 French national elections, perceptions of the French presidential candidates' positions on the ideological spectrum and respondents...