📊 Data Science Projects Collection

This repository contains a collection of data science and machine learning projects exploring topics in finance, analytics, clustering, classification, and real-world pattern discovery.
Each project is organized in its own folder with notebooks, datasets, and documentation.

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📁 Projects Overview

1. Inertia Trading – Boeing (BA) & S&P 500 (SPY)

Explores short-term trading strategies using:

• Rule-based intraday inertia signals
• Weekly machine learning labeling (kNN, SVM, Random Forest, etc.)
• K-means clustering and Hamming distance analysis across Dow Jones stocks
  Includes trading simulations, model comparisons, and visual insights.

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2. Banknote Authentication – k-NN & Logistic Regression

Using the UCI Banknote Authentication Dataset:

• Exploratory pairplots for real vs. fake notes
• Simple rule-based classifier
• Optimized k-NN model (k=3 → ~99.7% accuracy)
• Logistic Regression with coefficient interpretation
• Feature-importance analysis through exclusion tests

Focuses on understanding classifier behavior and feature influence.

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3. Food & Vitamins Analysis

Analysis of the Kaggle Food Nutrition dataset:

• Nutrient distributions across food categories
• Rule-based nutrient classifier
• Correlation analysis of vitamins/minerals
• Visual summaries and descriptive reporting

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🛠 Tech Stack

• Python, Pandas, NumPy
• scikit-learn, SciPy
• Matplotlib, Seaborn, Plotly
• Jupyter Notebook, Quarto
• Version control via GitHub

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📦 Repository Structure

Each project folder contains:

• Jupyter notebooks (.ipynb)
• Supporting datasets (CSV)
• Visualizations
• README files with explanations and findings