MahanFathi / CS231

Complete Assignments for CS231n: Convolutional Neural Networks for Visual Recognition

CS231n Assignment Solutions

Completed Assignments for CS231n: Convolutional Neural Networks for Visual Recognition Spring 2017.

I have just finished the course online and this repo contains my solutions to the assignments! What a great place for diving into Deep Learning. Big thanks to all the fellas at CS231 Stanford!

Find course notes and assignments here and be sure to check out video lectrues for Winter 2016 and Spring 2017!

Assignment 1:

• Q1: k-Nearest Neighbor classifier. (Done)
• Q2: Training a Support Vector Machine. (Done)
• Q3: Implement a Softmax classifier. (Done)
• Q4: Two-Layer Neural Network. (Done)
• Q5: Higher Level Representations: Image Features. (Done)

Assignment 2:

• Q1: Fully-connected Neural Network. (Done)
• Q2: Batch Normalization. (Done)
• Q3: Dropout. (Done)
• Q4: Convolutional Networks. (Done)
• Q5: PyTorch / TensorFlow on CIFAR-10. (Done in TensorFlow)

Assignment 3:

• Q1: Image Captioning with Vanilla RNNs. (Done)
• Q2: Image Captioning with LSTMs. (Done)
• Q3: Network Visualization: Saliency maps, Class Visualization, and Fooling Images. (Done in TensorFlow)
• Q4: Style Transfer. (Done in TensorFlow)
• Q5: Generative Adversarial Networks. (Done in TensorFlow)