# Automatically Answering and Generating Machine Learning Final Exams
Data and code for the paper "Automatically Answering and Generating Machine Learning Final Exams".

We present a new dataset of 646 questions from twelve final exams of MIT’s and Cornell's Introduction to Machine Learning courses and harvard's Machine Learning class. The dataset spans questions on the 17 machine learning topics covered in the courses: (1) regression, (2) classifiers, (3) logistic regression, (4) features, (5) loss functions, (6) neural networks, (7) convolutional neural networks (CNNs), (8) Markov decision processes (MDPs), (9) recurrent neural networks (RNNs), (10) reinforcement learning, (11) clustering, (12) decision trees (13) model selection, (14) ensemble methods, (15) Bayesian networks, (16) hidden Markov model, and (17) optimization. Summary statistics and details are available in Tables 3, 5, 6, 7, and 8 in the paper.

We provide code for running zero- and few-shot learning and for generating new questions as described in the paper.
