🎬 Netflix Content Type Classifier (EDA + ML) — by Umeir

This project explores and analyzes Netflix's titles dataset to uncover content trends through data cleaning, visual insights, and machine learning.
In the final stage, a model predicts whether a title is a Movie or TV Show based on specific features.

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📂 Table of Contents

1. Introduction
2. Data Cleaning
3. Exploratory Data Analysis (EDA)
4. Insights and Visualizations
5. Machine Learning - Predicting Movie vs TV Show
6. Dataset
7. Tools & Libraries
8. How to Run
9. Author

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1. Introduction

Netflix offers a massive collection of titles ranging from TV Shows to Movies.
The goal of this project is to:

• Understand the structure and trends in Netflix's content library
• Build a predictive model that classifies a title as a Movie or TV Show based on its duration, rating, and release year.

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2. Data Cleaning

• Removed null and duplicate values
• Transformed duration column to numeric
• Encoded categorical columns (type, rating) for modeling

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3. Exploratory Data Analysis (EDA)

• Analyzed distribution of Movies vs TV Shows
• Examined content release trends over time
• Investigated duration patterns and rating types

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4. Insights and Visualizations

• Visual graphs to uncover patterns in ratings, content duration, and content type
• Insights into trends in different regions and over different years
• Found correlations between release year, content duration, and type

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5. Machine Learning - Predicting Movie vs TV Show

A logistic regression model was trained on the following features:

• duration_num
• rating_encoded
• release_year

Steps:

• Applied train/test split (80% training / 20% testing)
• Trained a Logistic Regression classifier
• Evaluated using Accuracy, Classification Report, and Confusion Matrix

Model Accuracy: 99.8%

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Dataset

• 📦 Source: Netflix Titles Dataset on Kaggle
• Columns used: type, duration, rating, release_year

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Tools & Libraries

• Python 3
• Pandas, NumPy
• Matplotlib, Seaborn
• Scikit-learn
• Jupyter Notebook

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🛠️ How to Run

1. Clone the repository: git clone https://github.com/mumairrr/Netflix_Content_Type_Classifier_Umeir.git cd Netflix_Content_Type_Classifier_Umeir

2. Install required libraries: pip install -r requirements.txt

3. Launch Jupyter Notebook: jupyter notebook

Then open: 📄 Netflix_Content_Type_Classifier_Umeir.ipynb

📊 Dataset Netflix dataset from Kaggle - Netflix Shows

📄 Requirements All dependencies are listed in requirements.txt:

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🙋‍♂️ Author

Umeir Mohamed
Master’s Student in Data Science – Milano Bicocca University
LinkedIn | GitHub