To seek and maintain full-time position that offers professional challenges utilizing interpersonal skills, excellent time management and problem-solving skills.
FAKE NEWS DETECTION, Developed a robust system to classify news articles into 'real' or 'fake' categories. Objectively evaluated the accuracy of various models to ensure optimal news classification. Utilized two distinct datasets for real and fake news, leveraging technologies such as natural language processing and deep learning. Implemented LSTM (Long Short-Term Memory) networks, a subset of RNN, achieving a remarkable 97% accuracy in detection. Conducted comprehensive exploratory analysis to pinpoint linguistic patterns prevalent in deceptive content.
MEDICAL INSURANCE PRICE PREDICTION, Engineered a precise machine learning model to predict individual medical insurance costs. Capitalized on a comprehensive dataset containing demographic details, health attributes, and historical insurance rates to ensure reliable future cost estimations. Addressed existing methodological gaps, delivering a tool that enhances budgeting, decision-making, and medical expenditure planning for both individuals and organizations. Tested multiple supervised machine learning models including Linear Regression, Ridge Regression, Support Vector Regression, and Random Forest Regressor. Determined Random Forest Regressor as the paramount algorithm for accurate cost predictions based on historical data.
DATA STRUCTURES VISUALISER, Designed a dynamic and interactive website using the React framework and JavaScript, emphasizing the visualization of varied data structures. Led the creation of interactive visuals for prominent data structures such as arrays, linked lists, trees, and graphs. Integrated intuitive animations enabling users to visualize the storage, manipulation, and traversal of data elements within these structures. The website is built using responsive design principles, ensuring a seamless experience across various devices, from desktops to tablets and smartphones.