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
.csvfiles 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.