Zeta Learn: Minimalistic NumPy and Matplotlib ML Library

2 core Python dependencies, NumPy and Matplotlib, form the foundation of this minimalistic machine learning library. It provides a streamlined codebase for implementing and visualizing fundamental ML algorithms without the complexity of larger frameworks.

Use Cases

• Implement custom machine learning models using NumPy-based matrix operations.
• Generate performance plots and data visualizations using Matplotlib integration.
• Analyze the internal mechanics of ML algorithms by inspecting the minimalistic Python source code.

Strengths

• Built on NumPy for all matrix and vector calculations.
• Integrates Matplotlib for data and model performance visualization.
• Minimalistic Python architecture designed for readability and low dependency overhead.