Stanford CS231n Course: Convolutional Neural Networks for Visual Recogntion Assignments' Solutions.

The following repository has my solutions to all assignments of the CS231n Course offered by Stanford University (Spring 2020).

Assignments using PyTorch are only completed. TensorFlow related files are left unfinished.

You can see the course details using the link: http://cs231n.stanford.edu/

Spring 2017 Lecture videos are here: https://www.youtube.com/playlist?list=PL3FW7Lu3i5JvHM8ljYj-zLfQRF3EO8sYv

Assignment 1:

Q1: k-Nearest Neighbor classifier. (FINISHED)

Q2: Training a Support Vector Machine. (FINISHED)

Q3: Implement a Softmax classifier. (FINISHED)

Q4: Two-Layer Neural Network. (FINISHED)

Q5: Higher Level Representations: Image Features. (FINISHED)

Assignment 2:

Q1: Fully-connected Neural Network. (FINISHED)

Q2: Batch Normalization. (FINISHED)

Q3: Dropout. (FINISHED)

Q4: Convolutional Networks. (FINISHED)

Q5: PyTorch / TensorFlow on CIFAR-10. (FINISHED)

Assignment 3:

Q1: Image Captioning with Vanilla RNNs. (FINISHED)

Q2: Image Captioning with LSTMs. (FINISHED)

Q3: Network Visualization: Saliency maps, Class Visualization, and Fooling Images. (FINISHED)

Q4: Style Transfer. (FINISHED)

Q5: Generative Adversarial Networks. (FINISHED)