The document describes a project aimed at developing a machine learning model to automatically grade short written responses. The goal is to create a model that provides fairness, less human resource cost, and timely feedback compared to human grading. The model will be trained on a dataset of 17,000 student essays graded by humans. Features like part-of-speech tags, word lengths, spelling errors, grammar errors, term usage, and essay content will be engineered from the essays. Feature selection and various machine learning algorithms like KNN, Naive Bayes, decision trees, and ensemble models will be used to build and evaluate the final grading model.