• 😄 Pronouns: she/her
• 🔭 I’m a recent graduate from the Flatiron School's Data Science Immersive Program.
• 🌱 I’m currently prioritizing learning PySpark, SQL and Tableau.
• ❓ Ask me about EDA, GIS mapping, and machine learning through Python.
• 📫 How to reach me: email me at [email protected]
• 🌎Fun fact: I love learning languages on the side, I have studied Arabic for 3 years and before the pandemic lived in Cairo, Egypt.

California Reservoir Time Series Prediction- Link

• Built time series machine learning models to predict reservoir storage levels across California
• Created a seasonal auto-regressive, moving-average model using a grid search, resulting in predicted levels within 9% of actual.
• Used statsmodels, pmdarima, and sklearn to create and test SARIMA, SARIMAX, and HWES models across evaluation statistics.

Movie Recommendation System - Link

• Created a movie collaborative filtering recommendation system for users of a streaming service.
• Utilized Surprise machine learning libraries to find the best recommendation model using 600 users ratings across 100,000 movies.
• Chose a singular value decomposition model using a grid search, resulting in predicted ratings within 12% of actual ratings.

H1N1 Vaccine Analysis - Link

• Implemented machine learning models to predict respondents’ vaccination decision during the 2009 H1N1 pandemic.
• Chose logistic regression using a grid search, and used a pipeline, resulting in an 83% prediction accuracy score.
• Performed EDA and determined doctor opinion and personal opinion on H1N1 risk and vaccine efficacy were highest predictors.

Home Sales Analysis - Github Link Tableau Link

• Developed a multiple linear regression model with prediction accuracy within $100k of true price and 63% higher accuracy than baseline.
• Analyzed Pearson correlation of 20 different features for ~22,000 home sales from 2014-2015 in the Greater Seattle area.
• Built a Tableau Story overviewing the key statistics and areas of the real estate market.