🚀 Project 21: Sentiment Analysis using SentimentIntensityAnalyzer (VADER)

🗂️ Dataset Used 📘 Sentiment Analysis Dataset — Binary Classification 🔗 Available on Kaggle: https://www.kaggle.com/datasets/dineshpiyasamara/sentiment-analysis-dataset In this video, we’ll perform Sentiment Analysis on real-world text data using the SentimentIntensityAnalyzer from NLTK’s VADER module. We use the Sentiment Analysis Dataset — Binary Classification (from Kaggle) to analyze the polarity of tweets and classify them as Positive, Negative, or Neutral. This project is perfect for beginners in NLP and Data Science who want hands-on practice with text preprocessing, stopword removal, and sentiment scoring using Python. 📚 What You’ll Learn ✅ What Sentiment Analysis is in NLP ✅ How to clean text and remove stopwords ✅ Using NLTK’s SentimentIntensityAnalyzer for sentiment scoring ✅ Understanding compound scores (positive, negative, neutral) ✅ Applying the model to a Kaggle dataset ✅ Creating sentiment-based labels for each text #machinelearning #nlp #sentimentanalysis