The goal of the project is to classify “Amazon” reviews based on “helpful/unhelpful” votes, i.e. given a review, to predict if it is “helpful” or not.
The classification process in based on the number of “helpful/unhelpful” votes for each review in our dataset that contains hundreds of thousands of reviews.
After preprocessing of the data, we will compare between different Machine Learning models, some of them are relatively naïve and some are more complex. Also, we will do iterative process to examine the effect of changing the hyper-parameters of the models on their performance.
Furthermore, the project will provide practical experience in the domain of Machine Learning in general and Natural Language Processing in particular.