NLP Text Processing and Star Rating Analysis Application

A practical guide to applying NLP techniques for analyzing text and predicting star ratings.

Introduction

Natural Language Processing (NLP) is pivotal in deriving insights from text data. This tutorial demonstrates an end-to-end application where we process text reviews and predict their star ratings.

We will use Python, the pandas, nltk, sklearn, and matplotlib libraries for implementation. Key steps include:

• Text cleaning and tokenization.
• Exploratory Data Analysis (EDA).
• Sentiment-based feature engineering.
• Building and evaluating predictive models.

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Dataset and Preprocessing

We use a public dataset containing text reviews and star ratings. Download and load the dataset using pandas:

```python import pandas as pd

Load dataset

data = pd.read_csv(‘reviews.csv’) print(data.head())