Artificial Intelligence Intern
1. Developed a deep learning model for skin disease classification, achieving 97% accuracy across diverse skin types, thereby providing dermatologists with more inclusive diagnostic tools.2. Developed a machine learning model to predict heart attack risk using medical data (e.g., cholesterol levels, blood pressure) and demographic information (e.g., age, gender), achieving 95% accuracy with a Random Forest model.3. Developed an automated tool leveraging open-source technologies to analyse content and generate diverse, contextually relevant comments, enhancing user engagement and interaction.4. Conducted comprehensive COVID-19 data analysis using SQL, extracting valuable insights on the pandemic’s impact through detailed examination of geographic and temporal data.5. Performed an in-depth analysis of NREGA data using Tableau, evaluating program effectiveness, identifying regional disparities, and providing data-driven recommendations for policy optimization.6. Utilised data preprocessing and analysis skills to examine parameters such as job cards, workforce, and expenditure, guiding policymakers for scheme optimization.7. Developed actionable insights and presented findings to stakeholders, enhancing the overall understanding and effectiveness of data-driven decision-making processes.
