🐧 Predict penguin species using a machine learning app that analyzes physical traits and habitat for instant, insightful results.

An interactive Streamlit web application that uses a Random Forest classifier to predict penguin species based on real-time user inputs.

Demonstrating F# applications in Data Science — functional data analysis, cleaning, and visualization using Deedle & Plotly.NET. Explore how F#'s type safety, pipelines, and pattern matching create elegant data science workflows.

A Penguin Prediction Model

A reproducible exploratory data analysis (EDA) of the Palmer Penguins dataset using R. Features automated plot generation, data cleaning, and species differentiation insights.

Data cleaning, preprocessing, and class balancing of the Palmer Penguins dataset using Python (pandas, seaborn, scikit-learn, imbalanced-learn). Includes handling missing values, outliers, encoding, visualization, and SMOTE.

Exploratory data analysis and statistical tests on the 1973 New York AirQuality dataset and the Palmer Penguins dataset — visualizations, hypothesis testing, and insights.