Usman Waris
Data science and Machine Learning expert
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Usman is building their profile!
◆ "Do you want to stop losing customers before they leave? I built an end-to-end analytics tool that predicts customer churn with high precision.
➤ What this project delivers:
✔ Automated Risk Assessment: Upload your dataset and get instant predictions using Artificial Neural Networks (ANN).
✔ Strategic Segmentation: Automatically categorizes your user base into High, Moderate, and Low-risk groups.
✔ One-Click Reporting: Export high-risk customer lists directly to CSV for your marketing and sales teams.
✔ Interactive UI: A clean, user-friendly Streamlit dashboard designed for non-technical stakeholders to make data-backed decisions.
I specialize in bridging the gap between complex Deep Learning models and real-world business growth."
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➤ Overview
I developed a high-performance Computer Vision application designed to transform raw video footage into structured, actionable traffic data. This solution eliminates the need for manual counting and provides businesses with real-time insights into vehicle and pedestrian flow.
➤ The Problem & Solution
Manual traffic monitoring is slow, prone to error, and expensive. My application automates this entire process using State-of-the-Art Deep Learning (YOLO). It doesn’t just "see" the traffic; it measures it, graphs it, and exports it for professional reporting.
➤ Key Deliverables & Capabilities
⬥ Precision Multi-Object Tracking: High-accuracy detection of Cars, Bikes, Trucks, and Pedestrians.
⬥ Live Analytics Dashboard: Real-time visual graphs showing traffic intensity and peak congestion periods.
⬥ Automated Reporting: A one-click feature to convert visual detections into CSV or Excel data tables for business analysis.
⬥ Scalable Deployment: Built with Streamlit, making it accessible via a web browser without complex local installations.
➤ Tech Stack
⬥ AI/ML: Python, YOLOv11, OpenCV
⬥ Data Engineering: Pandas, NumPy
⬥ Web Framework: Streamlit (Custom UI Design)
⬥ Data Visualization: Plotly / Matplotlib
➤ Why This Matters for Your Business
Whether you are in Urban Planning, Logistics, or Retail Real Estate, knowing exactly how many vehicles or people pass a specific point is critical. This tool provides 24/7 monitoring capabilities at a fraction of the cost of traditional sensor hardware.
➤ 🔗 View the Source Code on GitHub: [https://github.com/Usman-Waris/YOLO-object-detection-traffic-detection-system- ]
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➤ Overview
I engineered a high-impact Machine Learning solution that enables businesses to move beyond "one-size-fits-all" marketing. By leveraging advanced clustering and predictive modeling, this application identifies distinct customer personas and predicts future behavior to optimize retention and sales strategies.
➤ The Problem & Solution
Many businesses struggle to identify who their most valuable customers are and why they leave. I built this Streamlit powered dashboard to automate the entire data science pipeline from cleaning raw data to generating interactive segments allowing stakeholders to make data-driven decisions in seconds.
➤ Key Deliverables & Capabilities
◆ Behavioral Segmentation: Uses unsupervised learning to group customers by purchasing patterns, demographics, and engagement levels.
◆ Churn Prediction Engine: Integrated XGBoost model to predict which customers are likely to stop using a service, allowing for proactive retention.
◆ Interactive BI Dashboard: A user-friendly Streamlit interface that turns complex data into clear, visual charts and heatmaps.
◆ Actionable Data Export: Direct integration for downloading segmented lists into CSV/Excel for immediate use in email marketing or CRM tools.
➤ Tech Stack
◆ Machine Learning: Clustring K-Means, Scikit-learn (T-SNE/ SGD)
◆ Data Science: Python, Pandas, NumPy
◆ Visualization: Plotly, Seaborn
◆ Deployment: Streamlit Cloud / GitHub
➤ Business Value
◆ This tool is designed for E-commerce, SaaS, and Retail brands looking to:
◆ Increase Customer Lifetime Value (CLV) by targeting the right segments.
◆ Reduce Churn Rates through early-warning predictive signals.
◆ Personalize marketing campaigns for higher conversion rates.
➤ 🔗 View the Source Code on GitHub: [https://github.com/Usman-Waris/customer-intelligence-app ]
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