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Merge pull request #36 from donnemartin/develop
Add reference to nlintz/TensorFlow-Tutorials
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README.md

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@@ -82,6 +82,11 @@ IPython Notebook(s) demonstrating deep learning functionality.
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### tensor-flow-tutorials
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Additional TensorFlow tutorials:
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* [pkmital/tensorflow_tutorials](https://github.com/pkmital/tensorflow_tutorials)
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* [nlintz/TensorFlow-Tutorials](https://github.com/nlintz/TensorFlow-Tutorials)
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| Notebook | Description |
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|--------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------|
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| [tsf-basics](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/deep-learning/tensor-flow-examples/notebooks/1_intro/basic_operations.ipynb) | Learn basic operations in TensorFlow, a library for various kinds of perceptual and language understanding tasks from Google. |
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| [tsf-gviz](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/deep-learning/tensor-flow-examples/notebooks/5_ui/graph_visualization.ipynb) | Learn about graph visualization in TensorFlow. |
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| [tsf-lviz](http://nbviewer.ipython.org/github/donnemartin/data-science-ipython-notebooks/blob/master/deep-learning/tensor-flow-examples/notebooks/5_ui/loss_visualization.ipynb) | Learn about loss visualization in TensorFlow. |
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Also check out another set of TensorFlow tutorials [here](https://github.com/pkmital/tensorflow_tutorials).
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### tensor-flow-exercises
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| Notebook | Description |
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* [Statistical Interference Using Computational Methods in Python](https://github.com/AllenDowney/CompStats) by Allen Downey
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* [TensorFlow Examples](https://github.com/aymericdamien/TensorFlow-Examples) by Aymeric Damien
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* [TensorFlow Tutorials](https://github.com/pkmital/tensorflow_tutorials) by Parag K Mital
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* [TensorFlow Tutorials](https://github.com/nlintz/TensorFlow-Tutorials) by Nathan Lintz
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* [Summer School 2015](https://github.com/mila-udem/summerschool2015) by mila-udem
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* [Kaggle](https://www.kaggle.com/)
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* [Yhat Blog](http://blog.yhat.com/)

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