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]