This is the second project of the Machine Learning Engineer Nanodegree by Udacity. The majority of the code was provided by Udacity, with a few sections completed by me as part of the exercise.

The Plagiarism Detector examines a text file and performs binary classification, labeling that file as either plagiarized or not, depending on how similar that text file is to a provided source text.

This project is broken down into three main notebooks:

Notebook 1: Data Exploration

• Not mandatory for the exercise and therefore not present on this repo

Notebook 2: Feature Engineering

• Clean and pre-processing of the text data.
• Definition of features for comparing the similarity of an answer text and a source text, and extract similarity features.
• Selection of "good" features by analyzing the correlations between different features.
• Creation train/test .csv files that hold the relevant features and class labels for train/test data points.

Notebook 3: Train and Deploy Your Model in SageMaker

• Upload the train/test feature data to S3 bucked in AWS SageMaker.
• Definition of a binary classification model and a training script.
• Training the model and deploy it using SageMaker.
• Evaluate the deployed classifier.

Please see the README in the root directory for instructions on setting up a SageMaker notebook and downloading the project files.