🧠 Sentiment Analysis Web App

An end-to-end Sentiment Analysis web application built using Python, scikit-learn, and Streamlit. This project covers the full machine learning pipeline: data preprocessing → model training → evaluation → deployment — all wrapped in a clean, interactive web UI.

🚀 Live Demo

🔗 Click here to try the app
💻 [View the code on GitHub] (https://github.com/prashant-guttedar/sentiment_analysis_project-using-NLP)

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🔍 Project Highlights

• ✅ Built using Python, Pandas, scikit-learn, and Streamlit
• 🔤 Advanced text preprocessing: handling contractions, lemmatization, stopwords optimization
• 🧠 Multiple ML models implemented:
  • Logistic Regression
  • Multinomial Naive Bayes
  • Decision Tree
• 📈 Evaluation using accuracy, confusion matrix, and classification report
• 📦 Model persisted using joblib and integrated with Streamlit app
• 🌐 Fully deployed and accessible via browser (Streamlit Cloud)

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🧰 Tech Stack

Area	Tools / Libraries
Language	Python
ML Models	scikit-learn
Text Processing	NLTK, re (regex), contractions
Vectorization	CountVectorizer, TfidfVectorizer, Word2Vec
Web App	Streamlit
Deployment	Streamlit Cloud / GitHub Pages

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🧪 Model Training & Evaluation

• Cleaned and tokenized movie review text
• Compared multiple ML models
• Selected best-performing model based on F1-score and overall accuracy
• Saved model using joblib for reuse

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🖥️ How to Run Locally

1. Clone the repo: bash git clone https://github.com/prashant-gutteda/sentiment_analysis_project-using-NLP.git cd sentiment_analysis_project-using-NLP

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