CODSOFT_Movie_Genre_Classification

Movie Genre Classification using TF-IDF and Machine Learning

🎬 Movie Genre Classification

A Machine Learning project that predicts the genre of a movie based on its plot summary using TF-IDF and classifiers like Naive Bayes, Logistic Regression, and Linear SVM.

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📌 Problem Statement

Create a model that predicts the genre of a movie based on its plot summary using NLP techniques.

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📂 Dataset

• Source: Kaggle - Genre Classification Dataset IMDB
• Files: train_data.txt, test_data.txt, test_data_solution.txt

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🛠️ Tech Stack

• Python
• Google Colab
• Scikit-learn
• TF-IDF Vectorizer
• Pandas, NumPy, Matplotlib, Seaborn

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⚙️ Models Used

Model	Accuracy
Naive Bayes	~52%
Logistic Regression	~58%
Linear SVM	~57%

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🔄 Steps

1. Load & explore the dataset
2. Clean and preprocess text
3. TF-IDF Vectorization
4. Train multiple ML models
5. Compare accuracies
6. Predict genre for new descriptions

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▶️ How to Run

1. Open movie_genre_classification.ipynb in Google Colab
2. Download the dataset from Kaggle
3. Run all cells step by step ##0R Run Google Collab Link:-https://colab.research.google.com/drive/1mMlIgvHBdjgu6fUP3qm2Sw4oTdqlWQLy?usp=sharing

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• 📊 Results

• Best Model: Logistic Regression with 58% accuracy
• Dataset is imbalanced (Drama & Documentary dominate)
• All 3 models used TF-IDF (10,000 features, bigrams)

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👤 Author

• Suhani Parveen
• GitHub: Suhani-ai-dev