Скачать или смотреть Learn Sentiment Analysis in Python | TextBlob, VADER & Naive Bayes Explained in Hindi

Want to analyze if a review is positive, negative, or neutral? In this fun and beginner-friendly tutorial, we’ll show you how to perform sentiment analysis using three powerful tools in Python:

✅ TextBlob – Simple and effective for quick sentiment scoring
✅ VADER – Perfect for social media and short texts
✅ Naive Bayes (with scikit-learn) – A machine learning approach using probability

What You'll Learn:
Installing TextBlob, VADER, and Scikit-learn
What TF-IDF means and how it's used
How Naive Bayes works using Bayes' Theorem
Hands-on coding examples with all three methods
Building your own sentiment classifier

🧠 QUIZ TIME – Test Your Knowledge!

1️⃣ TextBlob Question:
Q: If the polarity score is -0.8, what is the sentiment?
✅ Answer: C) Negative

2️⃣ VADER Question:
Q: What type of text is VADER best suited for?
✅ Answer: B) Social Media and Short Texts

3️⃣ Naive Bayes Question:
Q: What principle does Naive Bayes use?
✅ Answer: B) Probability and Bayes' Theorem

4️⃣ TfidfVectorizer Question:
Q: What does TfidfVectorizer() do?
✅ Answer: C) Converts text into numerical form

5️⃣ VADER Compound Score Question:
Q: If the compound score is 0.2, what is the sentiment?
✅ Answer: C) Positive

💡 Bonus Challenge:
Analyze the sentiment of your favorite movie review and share it in the comments! 🎬🔥

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