CS231n-Convolutional-Neural-Networks-Assignments

My solutions to the assignment of Stanford's course CS231n: Convolutional Neural Networks for Visual Recognition, Spring 2017.

If you are starting to work on this course you could work on the assignments of Spring 2019, you could find the assignments and some tutorial notebooks, also the Tensorflow notebooks for the assignments are in Tensorflow version 2 unlike Spring 2017.

The assignments details are listed below:

Assignment 1

• 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

Assigment 2

• Q1: Fully-connected Neural Network
• Q2: Batch Normalization
• Q3: Dropout
• Q4: Convolutional Networks
• Q5: PyTorch / TensorFlow on CIFAR-10 (Done using Tensorflow V1)

Assigment 3

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