Advtrix Learning 🚀

Welcome to Advtrix Learning, a comprehensive repository of AI-driven solutions, machine learning models, automation pipelines, and an interactive Streamlit app developedby applying the knowledge and skills gained during my Advtrix Internship experience, into a practical, production-ready application.

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📌 Overview

This repository delivers production-ready implementations for:

✅ Lead Scoring Model
Predicts the likelihood of lead conversion to optimize sales outreach.

✅ Customer Segmentation
Clusters customers based on behavioral and demographic data to enable personalized marketing strategies.

✅ Trend Forecasting
Applies time series models for predicting marketing and sales trends.

✅ Churn and Marketing Analysis
A unified analysis framework for customer churn, marketing spend impact, predictive modeling, and customer clustering.

✅ Terrag AI (Streamlit App)
An AI-powered interactive analytics app built with Streamlit for data exploration, lead scoring, segmentation, forecasting, and chat-based data insights.

✅ Automation Scripts
Automated workflows for data processing, generation, and analysis.

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👤 Project Structure

advtrix-learning/
│
├── notebooks/            # ML & data analysis notebooks
│   ├── data/             # Datasets for notebooks
│   ├── 01_lead_scoring_model.ipynb
│   ├── 02_customer_segmentation.ipynb
│   ├── 03_trend_forecasting.ipynb
│   └── 04_churn_and_marketing_analysis.ipynb
│
├── streamlit_app/        # Terrag AI - Streamlit app for data analytics
├── automation/           # Automation scripts for data generation & cleaning
├── requirements.txt      # Python dependencies
├── .gitignore            # Git ignored files
└── README.md             # Project documentation

🔔 Note: All datasets are stored under notebooks/data/.

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🔧 Tech Stack

• Python: Core programming language
• Scikit-learn, XGBoost, Prophet: Machine Learning & Forecasting
• Streamlit: Interactive UI for Terrag AI
• Pandas, NumPy, Matplotlib, Altair: Data processing and visualization
• GitHub: Version control and collaboration

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🚀 Getting Started

git clone https://github.com/MuhammadTahaNasir/advtrix-learning.git
cd advtrix-learning
pip install -r requirements.txt

To Run the Streamlit App

cd streamlit_app
streamlit run app.py

To Explore Notebooks

Launch Jupyter and navigate to the notebooks/ folder:

jupyter notebook

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📊 Datasets

All datasets (CSV files) are available under:

notebooks/data/

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🤝 Contributing

We welcome contributions! Fork the repository, submit PRs, or raise issues to collaborate.

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👤 Author

Muhammad Taha Nasir
🤖 AI Engineer
💻 Full Stack Developer

🔗 GitHub
🔗 LinkedIn

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