Stanford CS231n, 2018, assignments
Assignment#1
Q1: k-Nearest Neighbor classifier (20 points) : Done
The IPython Notebook knn.ipynb will walk you through implementing the kNN classifier.
Q2: Training a Support Vector Machine (25 points)
The IPython Notebook svm.ipynb will walk you through implementing the SVM classifier.
Q3: Implement a Softmax classifier (20 points)
The IPython Notebook softmax.ipynb will walk you through implementing the Softmax classifier.
Q4: Two-Layer Neural Network (25 points)
The IPython Notebook two_layer_net.ipynb will walk you through the implementation of a two-layer neural network classifier.
Q5: Higher Level Representations: Image Features (10 points)
The IPython Notebook features.ipynb will walk you through this exercise, in which you will examine the improvements gained by using higher-level representations as opposed to using raw pixel values.