Charmaine Manalac

Titanic Survival Prediction (TensorFlow, Pandas, Numpy, Matplotlib, Seaborn, scikit-learn)

• Developed a machine learning model to predict passenger survival on the Titanic using Python and popular libraries such as TensorFlow, pandas, and seaborn.
• Conducted data analysis and visualization, implemented a neural network, and achieved a 80% accuracy on the validation set to answer the Kaggle Titanic ML competition challenge.

Building A Retail Data Pipeline (ETL/Data Pipeline, Parquet Data Format)

• End-to-end data engineering project. Developed a data pipeline to analyze demand and supply around holidays for Walmart's expanding e-commerce business, accounting for 13% of total sales by the end of 2022.
• Executed data transformation tasks, including imputation, filtering, and monthly sales averaging, resulting in informed insights for optimizing sales strategies.