Following the course of Stanford CS231n: Convolutional Neural Networks for Visual Recognition, this repository is for my solutions for the assignments of the course.
- 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
- Q1: Image Captioning with Vanilla RNNs
- Extra Credit: Image Captioning with LSTMs
- Q2: Image Captioning with Transformers(PyTorch)
- Q3: Network Visualization(TensorFlow)
- Q4: Generative Adversarial Networks(TensorFlow)
- Q5: Self-Supervised Learning for Image Classification(PyTorch)
*Since the TensorFlow version of Assignment3 - Q3, Q4 are not provided in 2021, replaced with notebooks from 2020.
*Summaries for the lecutres are in my blog.
*2022-01-31, All works complete.