My solutions for stanford cs231n, deep learning for computer vision, spring 2021 version.
There are a bunch of .py files changed for the 3 assignments in addition to the completed notebooks. See them in one place in these commit diffs:
Quick links to completed .ipynb notebooks with output for each assignment:
- Q1: K-Nearest-Neighbor classifier
- Q2: Training a Support Vector Machine
- Q3: Implement a Softmax Classifier
- Q4: Two-Layer Neural Network
- Q5: Higher Level Representations: Image Features
- Q1: Multi-Layer Fully Connected Neural Networks
- Q2: Batch Normalization
- Q3: Dropout
- Q4: Convolutional Neural Networks
- Q5: TensorFlow on CIFAR-10
- Q5: PyTorch on CIFAR-10
- Q1: Image Captioning with Vanilla RNNs
- Q2: Image Captioning with Transformers
- Q3: Network Visualization: Saliency Maps, Class Visualization, and Fooling Images
- Q4: Generative Adversarial Networks
- Q5: Self-Supervised Learning for Image Classification
Original assignment code in initial commit.