Portfolio
Step into my data-driven journey! As an entry-level data analyst, my portfolio showcases the early strides in transforming raw data into valuable insights. Dive into projects that reflect my passion for deciphering patterns and making sense of information.
From data cleaning to visualization, explore how I apply analytical skills to tackle real-world challenges. Join me on this evolving adventure as I build a foundation in the dynamic realm of data analysis, eager to contribute fresh perspectives and insights to the ever-expanding data landscape
Focuses on developing a predictive model for COVID-19 ICU admissions, leveraging patient data to forecast the likelihood of intensive care unit admission. By employing advanced algorithms, the project aims to enhance medical resource allocation and patient care planning during the ongoing pandemic.
Utilized advanced machine learning techniques to classify health insurance plans based on multi-year issuer data. Achieved a remarkable 97% accuracy using K-Nearest Neighbors, optimizing model performance through hyperparameter tuning. This project provided critical insights into plan distributions, enabling data-driven decision-making in healthcare offerings.
Leveraged machine learning algorithms to predict loan default risks, achieving an 83% accuracy with the Decision Tree model. Conducted comprehensive data analysis and hyperparameter tuning, enabling effective risk assessment and informed decision-making in lending practices.
Assessing and improving the accuracy of movie and show reviews by implementing robust data cleaning and validation techniques. By addressing inconsistencies and anomalies in dataset, the project aims to enhance the reliability of the review system, providing users with more trustworthy and representative insights into the popularity and quality of movies and shows
Focuses on optimizing bank marketing strategies through predictive modeling. By analyzing customer data and behavior, the project aims to develop a model that identifies potential clients likely to respond positively to marketing campaigns, ultimately improving the efficiency and effectiveness of targeted outreach efforts for the financial institution.
Aimed to create a comprehensive database to manage and analyze pet-related transactions. By integrating SQL for data storage and Python for data manipulation and visualization, the project facilitates efficient tracking of sales trends, inventory management, and customer preferences, offering valuable insights for pet businesses
Through statistical analysis and visualization techniques, the project aims to provide a comprehensive understanding of player performance, team dynamics, and game outcomes, offering valuable perspectives for baseball enthusiasts, analysts, and strategists alike.
Through statistical analysis and visualization techniques, these projects aim to provide a comprehensive understanding of market performance, sales reports, and survival analysis, offering valuable perspectives for key stakeholders.
This predictive analytics BI project for Lemonade harnesses data insights to foresee trends and optimize business strategies in the insurance sector, empowering proactive decision-making and enhancing overall operational efficiency.
