Optimization Lab

Visualizing Numerical Optimization (GD vs Newton)

The Optimization Lab is a specialized benchmarking suite designed to analyze the behavior of optimization algorithms in Deep Learning landscapes.

Instead of duplicating the documentation here, I maintain the technical deep-dive, mathematical proofs, and live code directly on the repository to ensure it’s always up-to-date.

🚀 View Full Project & Code on GitHub

Project Highlights

Here is a glimpse of the results generated by the engine (fetched directly from the repository):

Newton's Method Convergence
Navigating the Rosenbrock Valley
The Local Minima Challenge

Technologies used: Python, NumPy, Streamlit, Plotly.