About me
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Lily Magliente.
Data Science. Python. SQL. Machine Learning. Statistics. Computer Vision. Math. Cloud Computing. Jokes.
My Experience
Began as a Data Scientist Analyst at Lockheed Martin
2020
2024
Graduated from The Pennsylvania State University with a Bachelor’s of Science in Data Science
Obtained a Master’s in Information and Data Science from University of California Berkeley
My Interests
Leverage the power of graphs and tables to present the data’s insights in a comprehensible
manner
ML goes beyond using the sklearn library; it requires thorough data engineering and exploration to develop optimal models.
Data Visualization
Machine Learning
I aim to tell a compelling story to present analysis
Data Analytics
Statistics
From Regression to Probability, statistics is foundational data science
Customer Relationships
Connecting with others and understanding the problems they outline is foundational to a successful project
My Projects
Conduct Data Analysis and Machine Learning modeling in Databricks. Exhibits data exploration, cleansing, engineering as well as Machine Learning modeling, hyperparameter tuning. Official final report here.
This project analyzes the 2024 Pikes Peak 10k race results, focusing on Exploratory Data Analysis, data cleansing, and visualizations. It compares race times across divisions and genders, visualizes these differences.
This project leverages Imagenette images to investigate the synergy between image pre-processing, feature extraction, and classifiers in achieving accurate classifications. We explore feature extraction methods and different types of classifiers (with hyper parameter tuning) for optimal results.