Math Learning Repository

A repository for learning mathematics through interactive Python notebooks.

Structure

• probability/ - Probability theory and statistics concepts

Setup

Local Development (with uv)

This project uses uv for fast, reliable dependency management.

1. Install uv (if not already installed):

   curl -LsSf https://astral.sh/uv/install.sh | sh

2. Create and activate virtual environment:

   uv venv
   source .venv/bin/activate  # On Windows: .venv\Scripts\activate

3. Install dependencies:

   uv pip install -r requirements.txt

4. Launch Jupyter:

   jupyter lab

   or

   jupyter notebook

Kaggle

To use these notebooks on Kaggle:

1. Upload the notebook file (.ipynb) to Kaggle
2. The required packages (numpy, scipy, matplotlib, pandas, etc.) are pre-installed on Kaggle
3. For any additional dependencies, use:

   !pip install -r requirements.txt

Dependencies

• numpy - Numerical computing
• scipy - Scientific computing and statistics
• sympy - Symbolic mathematics
• matplotlib - Plotting and visualization
• seaborn - Statistical data visualization
• plotly - Interactive plots
• pandas - Data manipulation and analysis
• jupyter/jupyterlab - Interactive notebook environment

Usage

Each topic folder contains numbered notebooks that can be worked through sequentially. The notebooks include:

• Theoretical explanations
• Code examples
• Visualizations
• Practice exercises

Contributing

This is a personal learning repository, but suggestions and corrections are welcome!