bentrevett
diff --git a/‎5 - ResNet.ipynb
-588 b/‎5 - ResNet.ipynb
-588
diff --git a/‎README.md
+9-2 b/‎README.md
+9-2
diff --git a/‎4 - VGG.ipynb renamed to ‎misc/4 - VGG.ipynb b/‎4 - VGG.ipynb renamed to ‎misc/4 - VGG.ipynb
diff --git a/‎misc/5 - ResNet.ipynb
+2,222 b/‎misc/5 - ResNet.ipynb
+2,222
diff --git a/‎6 - ResNet - Dogs vs Cats.ipynb renamed to ‎misc/6 - ResNet - Dogs vs Cats.ipynb b/‎6 - ResNet - Dogs vs Cats.ipynb renamed to ‎misc/6 - ResNet - Dogs vs Cats.ipynb
diff --git a/‎conv order.ipynb renamed to ‎misc/conv order.ipynb b/‎conv order.ipynb renamed to ‎misc/conv order.ipynb
diff --git a/‎download_dogs-vs-cats.sh renamed to ‎misc/download_dogs-vs-cats.sh b/‎download_dogs-vs-cats.sh renamed to ‎misc/download_dogs-vs-cats.sh
diff --git a/‎process_dogs-vs-cats.py renamed to ‎misc/process_dogs-vs-cats.py b/‎process_dogs-vs-cats.py renamed to ‎misc/process_dogs-vs-cats.py
@@ -25,7 +25,13 @@ pip install torchvision
 * 2 - [LeNet](https://github.com/bentrevett/pytorch-image-classification/blob/master/2%20-%20LeNet.ipynb) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github.com/bentrevett/pytorch-image-classification/blob/master/2%20-%20LeNet.ipynb)
 
     In this tutorial we'll implement the classic [LeNet](http://yann.lecun.com/exdb/lenet/) architecture. We'll look into convolutional neural networks and how convolutional layers and subsampling layers work.
-    
+
+### TODO
+
+See `misc` folder for out of date implementations of the following:
+- AlexNet 
+- VGG
+- ResNet
 
 ## References
 
@@ -37,4 +43,5 @@ Here are some things I looked at while making these tutorials. Some of it may be
 - https://distill.pub/2016/misread-tsne/
 - https://towardsdatascience.com/visualising-high-dimensional-datasets-using-pca-and-t-sne-in-python-8ef87e7915b
 - https://github.com/activatedgeek/LeNet-5
-- https://github.com/ChawDoe/LeNet5-MNIST-PyTorch
+- https://github.com/ChawDoe/LeNet5-MNIST-PyTorch
+- https://github.com/kuangliu/pytorch-cifar