TECH PROJECTS

- Developed an interactive Power BI dashboard to visualize startup investment trends in India by integrating data on the number of startups, total investment, investor activity, and popular domains.
- Analyzed key metrics such as the rise in investments in companies like Flipkart and Rapido, and identified the dominance of Ecommerce and Consumer Internet sectors.
- The dashboard provided valuable insights, highlighting trends like the decrease in investments during 2020 and the concentration of startups, effectively guiding strategic decisions.

- Developed a comprehensive Power BI dashboard to analyze flight trends and airline performance in India by incorporating data on ticket prices, popular airlines, flight durations, and destinations.
- Highlighted key insights such as Airlines collecting the most ticket revenue and the highest ticket prices location.
- The dashboard provided actionable insights into booking patterns, airline performance, and popular routes, enabling better strategic decision-making for airline operations and marketing efforts.

- Built a T20 score prediction web application by refining datasets through the removal of outliers and irrelevant features, improving model accuracy and reducing training time.
- Implemented an XGBoost Regressor model, achieving 98% accuracy with a mean absolute error of 1.73 runs.
- Led to a highly precise prediction tool with 98% precision, effectively enhancing the accuracy and efficiency of T20 score forecasts

- Developed and optimized a web application for time series forecasting by implementing advanced feature extraction and data preprocessing techniques.
- Enhanced model performance through hyperparameter tuning, resulting in a 2% improvement in accuracy and a 2% reduction in training time.
- The application achieved a 4% accuracy improvement over traditional forecasting methods, significantly boosting prediction reliability

- Developed a Random Forest Classifier for heart disease prediction by streamlining data cleaning processes with Python scripts, reducing manual effort by 5%.
- Achieved a 98% accuracy rate, with 97% precision and recall on test data.
- This resulted in a highly accurate and efficient model, significantly improving prediction capabilities.