My work through to the assignments of the 2017 iteration of CS231n: Convolutional Neural Networks for Visual Recognition course.
I am grateful to Stanford for making the course resources available to the public.
- Q1: k-Nearest Neighbor classifier. (Done)
- Q2: Training a Support Vector Machine. (Done)
- Q3: Implement a Softmax classifier. (Done)
- Q4: Two-Layer Neural Network.
- Q1: Fully-connected Neural Network.
- Q2: Batch Normalization.
- Q3: Dropout.
- Q4: Convolutional Networks.
- Q5: TensorFlow on CIFAR-10.
- Q1: Image Captioning with Vanilla RNNs.
- Q2: Image Captioning with LSTMs.
- Q3: Network Visualization: Saliency maps, Class Visualization, and Fooling Images.
- Q4: Style Transfer.
- Q5: Generative Adversarial Networks.