Update README.md

README.md

@@ -61,6 +61,7 @@ The following examples are coming from [TFLearn](https://github.com/tflearn/tfle
 - [Network in Network](https://github.com/tflearn/tflearn/blob/master/examples/images/network_in_network.py). 'Network in Network' implementation for classifying CIFAR-10 dataset.
 - [Alexnet](https://github.com/tflearn/tflearn/blob/master/examples/images/alexnet.py). Apply Alexnet to Oxford Flowers 17 classification task.
 - [VGGNet](https://github.com/tflearn/tflearn/blob/master/examples/images/vgg_network.py). Apply VGG Network to Oxford Flowers 17 classification task.
+- [VGGNet Finetuning (Fast Training)](https://github.com/tflearn/tflearn/blob/master/examples/images/vgg_network_finetuning.py). Use a pre-trained VGG Network and retrain it on your own data, for fast training.
 - [RNN Pixels](https://github.com/tflearn/tflearn/blob/master/examples/images/rnn_pixels.py). Use RNN (over sequence of pixels) to classify images.
 - [Highway Network](https://github.com/tflearn/tflearn/blob/master/examples/images/highway_dnn.py). Highway Network implementation for classifying MNIST dataset.
 - [Highway Convolutional Network](https://github.com/tflearn/tflearn/blob/master/examples/images/convnet_highway_mnist.py). Highway Convolutional Network implementation for classifying MNIST dataset.