YashArote/gradient-descent-visualizer
A fast, interactive tool to visualize how different gradient descent algorithms (like vanilla gradient Descent, Momentum, RMSprop, Adam, etc.) navigate complex loss surfaces in real time.
This tool helps machine learning students and practitioners visually understand how different optimization algorithms navigate complex 'loss surfaces'. You input a mathematical function representing a loss surface and choose an optimizer, then observe its path in a real-time 3D visualization. It's designed for anyone learning or working with machine learning models who needs to grasp the mechanics of optimizers like Adam or SGD.
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Use this if you are studying or teaching machine learning and want to gain an intuitive understanding of how optimizers adjust model parameters to find the best solution.
Not ideal if you are looking for an optimizer to directly apply to your existing machine learning model or dataset.
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Language
JavaScript
License
MIT
Category
Last pushed
May 12, 2025
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