A cross-platform Self-Executable Markdown runbook that provides a complete system diagnostics dashboard directly in the terminal. Audit CPU, memory, disk utilization, network latency, active development ports, and overall system health through an interactive workflow. Designed for developers and DevOps engineers, it requires only Node.js and works on Windows, macOS, and Linux without external dependencies.

Fully fledged document for wave eq

A practical guide to dimensionality reduction using PCA. Learn how to compress high-dimensional datasets (100+ features) into 2-3 principal components without losing critical variance. Includes: mathematical intuition (covariance matrices, eigenvectors), implementation patterns (scikit-learn, TensorFlow), when to use PCA vs. other reduction techniques (t-SNE, UMAP), and production gotchas (scaling requirements, interpretation challenges). Real examples: image compression, feature engineering for faster models, visualization of complex datasets. Code snippets for training/inference pipelines.