🧠 Customer Segmentation Analysis — Ananda Swaroop

Welcome to the Data Analytics repository by Ananda Swaroop.
This repository focuses on customer segmentation using unsupervised machine learning techniques to enhance targeted marketing strategies for businesses.

🌐 Live App

Explore the live Streamlit application here:
👉 https://anandasigmaapp-dopdnjyymbvuvsjemcqhlv.streamlit.app/

Interact with clustering results, visualize customer segments, and extract actionable insights from high-dimensional data.

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🧾 Project Description

This project applies machine learning to identify distinct customer groups using behavior and demographic data. It is designed to support:

• Personalized marketing strategies
• Data-driven customer segmentation
• Cluster-based analytics for strategic decision-making

The pipeline includes:

• Data cleaning and preprocessing
• Feature scaling and engineering
• Dimensionality reduction (PCA, t-SNE)
• Clustering (K-Means)
• Visual analytics and deployment via Streamlit

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🧠 Core Concepts Used

• Unsupervised Learning
• Principal Component Analysis (PCA)
• t-distributed Stochastic Neighbor Embedding (t-SNE)
• K-Means Clustering with Elbow & Silhouette Score
• Visual Analytics & Interpretation

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🗂️ Repository Structure

data_analytics_anandaswaroop/
│
├── data/              # Sample datasets and raw input data
├── notebooks/         # Jupyter notebooks for analysis and tutorials
├── requirements.txt   # List of Python dependencies
└── README.md          # Project documentation

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🚀 Getting Started

1. Clone the repository

   git clone https://github.com/ANANDA-SWAROOP/data_analytics_anandaswaroop.git
   cd data_analytics_anandaswaroop

2. Install dependencies

   pip install -r requirements.txt

3. Explore the notebooks

   • Open the notebooks/ folder to find step-by-step tutorials and analysis examples.

4. Run scripts

   • Python scripts for various tasks can be found in the scripts/ directory.

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🔧 Technologies Used

• Python (Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn)
• Jupyter Notebook
• Git & GitHub

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📈 Example Use Cases

• Cleaning and preprocessing CSV datasets
• Visualizing trends and outliers in data
• Building regression and classification models
• Automating analysis tasks

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📝 Contributing

Contributions are welcome!
If you'd like to improve the code, add new notebooks, or fix issues, feel free to submit a pull request.

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📮 Issues & Support

If you encounter any problems or have questions, please open an issue.

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🙌 Author

ANANDA SWAROOP
Connect on GitHub