I'm Abishek Narayan V

Objective: Develop a virtual mouse system that uses hand gestures to control cursor movement and perform basic computer actions without hardware like a traditional mouse.

Key Features:

• Utilizes computer vision and color detection to track hand gestures with a webcam.
• Supports basic operations such as cursor movement, left-click, drag-and-drop, and file transfer between connected systems.
• Implemented with Python and OpenCV, leveraging adaptive algorithms to detect hand regions and control mouse actions.
• Performance measured with accuracy in hand gesture recognition for different commands, visualized using success rate metrics.

Future Enhancements: Optimizing accuracy under varying lighting conditions and expanding to mobile platforms, where gestures could replace traditional touchscreen interactions.

Objective: Forecast health insurance premium eligibility using advanced machine learning algorithms, providing a data-driven approach for personalized insurance policies.

Key Features:

• Data Collection: Acquired diverse insurance datasets from multiple sources, emphasizing quality for accurate predictions.
• Data Preprocessing: Employed techniques to clean data, remove null values, and scale features using LabelEncoder and MinMaxScaler.
• Feature Extraction: Identified and extracted critical attributes (e.g., age, gender, smoking status) influencing premium rates.
• Algorithms: Implemented supervised learning algorithms, focusing on Linear Regression, Stochastic Gradient Descent, and Multi-layer Perceptron (MLP) for optimal accuracy.
• Performance Metrics: Evaluated model accuracy and stability with metrics like accuracy scores and a confusion matrix, achieving high predictive reliability.

Implementation Highlights:

• Designed a modular system architecture with Python and Scikit-learn for streamlined processing.
• Utilized machine learning to automate data insights, significantly reducing manual effort in policy prediction.
• Developed UML, sequence, and class diagrams to document and visualize system workflow, supporting maintainability and scalability.

Future Enhancements: Integrating blockchain for data security, testing algorithms like Logistic Regression for improved model performance, and adapting the system for mobile platforms to expand accessibility.