● Collaborated with the data science team to Introduce a Recommendation System for a Video On Demand platform and enhanced user numbers by 18%. ● Employed data visualization and statistical analysis models to uncover trends in data, including Matplotlib and Seaborn, accelerating data-driven solutions discovery by 20%. ● Engineered the recommendation system using a robust tech stack, employing Python, Django, PostgreSQL, TensorFlow, Pandas, and NumPy. ● Achieved a signicant 30% increase in average monthly viewing time among users, showcasing the impact of targeted content strategies.

● Innovated and developed a decision-making system for diagnosing Parkinson's disease using deep neural networks and machine learning techniques, boosting the prediction accuracy by 93% and 90% increase in disease severity classication. ● Cleaned data to remove irrelevant data, used Time Series Analysis techniques, and visualized data to recognize data patterns, resulting in a 15% increase in accuracy. ● Implemented and crafted the system utilizing an advanced toolkit comprising Python, PostgreSQL, TensorFlow, PyTorch, SciPy, NumPy, Matplotlib, and Pandas.