Notes for the Practical Deep Learning Series
This repo contains workshop notes and code from the Practical Deep Learning Series with the Toronto Data Literacy Group.
Session 1 discuses background theory for artificial neural networks (ANNs), deep learning, and computation graph based libraries, particularly Google's TensorFlow.
Session 2 introduces the ANNs covered in session 1 in the form of TensorFlow code.
The CC-BY-ND license applies to the workshop notes only, not the code. The code is licensed under the MIT three-clause license (included here at in each source file) where applicable. The code in the file "input_data.py" found in Session1 is redistributed verbatim from Google's TensorFlow tutorial where it appears to be unlicensed. This code appears to originate with Yann LeCun.
This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License.
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Copyright (c) 2015 Robert A. Brown (Github)
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