Classification Projects
Prediction projects for categorical outcomes using supervised machine learning
Hi, my name is Lissette.
I am a mathematician building a portfolio in Data Analytics, Data Science, and Data Engineering foundations.
Regression Projects
Prediction projects for continuous outcomes such as prices, duration, demand, and traffic waiting time
Unsupervised Learning Projects
Projects focused on clustering, segmentation, dimensionality reduction, and hidden pattern discovery
NLP Projects
Future projects for text analytics, language data preprocessing, and NLP model interpretation
SQL Projects
API-to-SQLite analytics projects using SQL, validation checks, and visual summaries
Dashboard Projects
Interactive analytics projects built with Power BI, Python, Streamlit, and visualization libraries
Methods & Concepts
A growing collection of the statistical, machine learning, and data engineering concepts I use across my portfolio projects.
This section connects theory with practice: model evaluation, feature engineering, data leakage, cross-validation, class imbalance, regression metrics, clustering methods, and other ideas that guide my project decisions.
The goal is not to document everything I study, but to make visible how I think through data problems and turn technical concepts into practical analysis.