This repository contains a customer sentiment analysis project using Python, TextBlob, and WordCloud. It classifies customer reviews into Positive, Negative, or Neutral categories and visualizes sentiment insights through a Word Cloud. Technologies used include Pandas, Matplotlib, and WordCloud.
From the README
Sentiment-Analysis Customer Sentiment Analysis using Word Cloud Project Overview A simple NLP project that analyzes customer reviews using Python and TextBlob. Reviews are classified as Positive, Negative, or Neutral, and a Word Cloud is generated to identify the most common words in negative reviews. --- 📊 Sentiment Distribution This chart shows the overall distribution of customer sentiments. --- ☁️ Negative Review Word Cloud The word cloud highlights the most frequently used words in negative customer reviews, making it easier to identify common complaints. --- 🛠️ Technologies Used • Python • Pandas • TextBlob • Matplotlib • WordCloud --- 📌 Key Learning • Performed...
Skills
- Jupyter Notebook
- customer-reviews
- data-analysis
- data-visualization
- jupyter-notebook
- machine-learning
- nlp
- python
- sentiment-analysis
- textblob
- wordcloud
