Difference between revisions of "Tutorial: TensorFlow References"

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(Intro to ML, Google video)
(Intro to ML, Google video)
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=References & Tutorials=
 
=References & Tutorials=
 
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==Intro to ML, Google video==
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==Intro to Machine Learning and TensorFlow, Google video==
 
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<center><videoflash>vQtxTZ9OA2M</videoflash></center>
 
<center><videoflash>vQtxTZ9OA2M</videoflash></center>

Revision as of 11:03, 6 August 2016

--D. Thiebaut (talk) 12:00, 6 August 2016 (EDT)


References & Tutorials


Intro to Machine Learning and TensorFlow, Google video



This is a very good approach to TensorFlow which uses the wine data from UC Irvine Machine Learning repository. It uses the red wine data (winequality-red.csv). It starts with a 30-minute math tutorial presented by jenhsin0@gmail.com, and it covers entropy, variable dependency, dimensionality reduction, graph representation of models, activation functions in neural nets, loss functions, and gradient descent. After a 10-minute pause (which is part of the video), the next speaker starts with a Jupyter notebook exploring various aspects of the wine-quality data. The notebook and associated data are available from this github repository.