updated readmes

Author: kwinkunks

1808_Neural_networks/README.md

@@ -1,6 +1,6 @@
-# Neural Networks
+# Neural networks
 
-This tutorial serves as a deep look at the simplest of neural networks, the multilayer perceptron. The [manuscript notebook](https://github.com/seg/tutorials-2018/blob/master/1808_Neural_Network/manuscript.ipynb) uses no dependencies other than [Numpy](http://www.numpy.org/) to build up a neural network, train it to approximate a sine function, and then predict values inside (and outside) the domain of interest, [0, 2 $\pi$].
+This tutorial serves as a deep look at the simplest of neural networks, the multilayer perceptron. The [manuscript notebook](https://github.com/seg/tutorials-2018/blob/master/1808_Neural_Network/manuscript.ipynb) uses no dependencies other than [Numpy](http://www.numpy.org/) to build up a neural network, train it to approximate angle-dependent seismic reflectivity, and then predict values inside (and outside) the domain of interest.
 
 There's a code block which uses [tqdm](https://pypi.org/project/tqdm/) to render a progress bar to screen during training. To install tqdm:
 
@@ -14,3 +14,4 @@ And to plot the results you'll need [matplotlib](https://matplotlib.org/2.0.0/us
 
 * Thanks to [Expero](https://experoinc.com) for encouraging me to continue to publish.
 * Thanks to [Matt Hall](https://agilescientific.com/who/) for continuously pushing our professional community to modernize with efforts like the one you're reading now.
+* Thanks to Lukas Mosser and Jesper Dramsch for useful comments on an earlier version of this manuscript.

README.md

@@ -24,8 +24,8 @@ For more in-depth hints on getting started, see Hall, M (2016). A user guide to
 - [Other Notebooks](https://github.com/seg/tutorials-2018/tree/master/1806_Time-frequency)
 
 ## August 2018
-- [Neural Networks]() by Graham Ganssle
-- [Manuscript as Jupyter Notebook](https://github.com/seg/tutorials-2018/blob/master/1808_Neural_Network/manuscript.ipynb)
+- [Neural networks]() by Graham Ganssle
+- [Manuscript as Jupyter Notebook](https://github.com/seg/tutorials-2018/blob/master/1808_Neural_networks/Manuscript.ipynb)
 
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