🕵️ Introduction

We all refer to reviews and ratings for movies & shows, either on IMDB or through our friends before we binge them. In this assignment, you’re tasked with identifying the rating of a review using sentiment analysis.

The training dataset consists of {sentence id, review, rating}. Given a review, your neural network should be able to assign a rating score between 1 to 5 - low to high, respectively.

Do note:

• Perform sentiment analysis using a neural network with just one input and output layer (with softmax as activation function).
• You’re not allowed to have hidden layers.
• You will be working in & making submission through a notebook. You can follow the instructions in the starter code. You have to use it to train, predict & submit.

💾 Dataset

The dataset contains training data and test data. You can find it under Resources.

📁 Files

• train.csv - (50000 samples) This file contains training data with sentence ids, reviews & corresponding ratings (1 to 5).
• test.csv - (10000 samples) This file contains test data with sentence ids & reviews.

🚀 Submission

Submissions will be made through the notebook following the instructions in the starter code.

🖊 Evaluation Criteria

The evaluation will be done according to the following criterion:

• F1 score (Harmonic Mean of precision & recall)

📱 Contact

• DL for NLP TAs