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|Has keywords=Accelerator, Demo Day, Google Result, Word2vec, Tensorflow
|Has project status=Active
|Is dependent on=Accelerator Seed List (Data),Demo Day Page Parser
}}
==Project==
This is a tensorflow project that classifies webpages as either a demo day page or not. Not sure exactly the format of the input and output of the program. The classifier itself should take the output of Peter's DemoDayHits.py program and output whether the page is a demo day page. It is trained on a file outputted by DemoDayHits.py and a hand-classified set of google results, some of which are demo day pages. It may later take other inputs, such as the text of the page itself.
A demo day page is an advertisement page for a "demo day," which is a day that cohorts graduating from accelerators can pitch their ideas to investors. These demo days give us a good idea of when these cohorts graduated from their accelerator.
*https://machinelearnings.co/tensorflow-text-classification-615198df9231
*http://www.wildml.com/2015/12/implementing-a-cnn-for-text-classification-in-tensorflow/
*https://stats.stackexchange.com/questions/181/how-to-choose-the-number-of-hidden-layers-and-nodes-in-a-feedforward-neural-netw
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