Charmaine Vinarta

Projecting High ROI Degrees (R |tidyr, dplyr, readr, ggplot2, cluster, factoextra)

• Utilized ggplot2 to create scatter plots, visualizing relationships, generated line plots using geom_line to connect data points, depicting the progression of salary percentiles
• Applied the k-means clustering algorithm to group data points and identified the optimal number of clusters using the Elbow Method, Silhouette Method, and Gap Statistic Method

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)

• 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.