I'm just another geek trying to learn computer vision from Stanford's CNN course :)
The solutions are to the 2020 version of assignments (most notable differences are in assignment 3 )
- Fully-connected Neural Network
 - Batch Normalization
 - Dropout
 - Convolutional Networks
 - TensorFlow on CIFAR-10
 
- Image Captioning with Vanilla RNNs
 - Image Captioning with LSTMs
 - Network Visualization: Saliency maps, Class Visualization, and Fooling Images
 - Style Transfer
 - Generative Adversarial Networks
 
Feel free to use this work as long as you refrence this repo.
Contact: [email protected]