Zamzam Abdirizak Ali

Played a key role in creating and managing financial portfolios for clients, utilizing Microsoft Power BI.

• Responsibilities: Worked with complex datasets from client companies to track inventory, sales, and profits. Employed Power BI to analyze and present financial insights in a user-friendly manner.
• Training: Received hands-on training under the guidance of a Power BI specialist, acquiring skills essential for effective data visualization and business intelligence.
• Impact: Contributed to optimizing financial tracking systems, ensuring accuracy and efficiency in monitoring client portfolios. Enhanced practical skills in data analysis and visualization within a professional setting.

• Focused on classifying neutron stars using Naïve Bayes, LDA, and Logistic Regression models, trained on a dataset with eight relevant features
• Logistic Regression emerged as the most accurate model, achieving 98.1% accuracy, 0.981 F1 score, and 0.976 AUC score in distinguishing pulsars from non-pulsars
• Demonstrated expertise in prediction and classification models, data analysis, model development, and providing valuable insights into star classification.

• Explored machine learning techniques for prediction and classification using pollution data in Delhi
• Established a strong linear relationship between PM2_5 and PM10 pollutants through a simple linear regression model
• Developed a comprehensive multiple linear regression model to predict NO2 pollutant, achieving an R-squared value of 0.84 and identifying key predictors

• Metropolitan police data on stolen animals analysis, Analyzed a 12-year government dataset on stolen animals in London, conducting comprehensive data cleaning and organization to ensure data accuracy
• Developed visualizations, including figures showcasing trends in the number of stolen animals over time and across different boroughs.
• Presented findings and highlighted significance of results.