{"id":14977286,"url":"https://github.com/hahnec/optimizay","last_synced_at":"2025-10-11T09:17:53.915Z","repository":{"id":107359186,"uuid":"488765128","full_name":"hahnec/optimizay","owner":"hahnec","description":"collection of numerical optimization methods 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Optimizay\n\nThis repository contains a collection of mathematical optimization algorithms demonstrating underlying concepts in an interactive manner using Jupyter notebooks with Binder support: \n\n[![badge](https://img.shields.io/badge/launch-binder-E66581.svg?style=flat-square\u0026logo=data:image/png;base64,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)](https://mybinder.org/v2/gh/hahnec/optimizay/master?urlpath=lab)\n\nThe content list is given below and subject to further expansion:\n\n1. [Univarite Newton-Raphson Minimization](01_univar_newton.ipynb)\n\n    \u003ca href=\"01_univar_newton.ipynb\"\u003e\u003cimg src=\"./img/univar_loss_plot.png\" width=\"300px\"\u003e\u003c/a\u003e\n\n2. [Bivariate Gradient Descent vs. Newton-Raphson](02_bivar_newton_vs_descent.ipynb)\n\n    \u003ca href=\"02_bivar_newton_vs_descent.ipynb\"\u003e\u003cimg src=\"./img/bivar_min.png\" width=\"350px\"\u003e\u003c/a\u003e\n\n3. [Bivariate Newton Root-finding](03_bivar_newton_root.ipynb)\n\n    \u003ca href=\"03_bivar_newton_root.ipynb\"\u003e\u003cimg src=\"./img/polynom_intersect.png\" width=\"350px\"\u003e\u003c/a\u003e\n\n4. [Conjugate Gradient](04_conjugate_gradient.ipynb)\n    \n    \u003ca href=\"04_conjugate_gradient.ipynb\"\u003e\u003cimg src=\"./img/cg-fit_anim.gif\" width=\"350px\"\u003e\u003c/a\u003e\n\n5. [Gauss-Newton vs. Levenberg-Marquardt](05_gna_vs_lma.ipynb)\n\n    \u003ca href=\"05_gna_vs_lma.ipynb\"\u003e\u003cimg src=\"./img/lm-fit_anim.gif\" width=\"350px\"\u003e\u003c/a\u003e\n\n6. [Stochastic Gradient Descent (SGD)](06_stochastic_gradient.ipynb)\n\n    \u003ca href=\"06_stochastic_gradient.ipynb\"\u003e\u003cimg src=\"./img/sgd_anim.gif\" width=\"350px\"\u003e\u003c/a\u003e\n   \n7. [Feature Engineering - Titanic](07_feat_eng_titanic.ipynb)\n\n    \u003ca href=\"07_feat_eng_titanic.ipynb\"\u003e\u003cimg src=\"https://upload.wikimedia.org/wikipedia/commons/4/45/1912_Titanic_Departure_Colorized.jpg\" width=\"350px\"\u003e\u003c/a\u003e\n\n8. [Expectation Maximization](08_em.ipynb)\n\n    \u003ca href=\"08_em.ipynb\"\u003e\u003cimg src=\"./img/em-fit_anim.gif\" width=\"350px\"\u003e\u003c/a\u003e\n\n\nCredits\n=======\n\n### Author\n\n[Christopher Hahne](http://www.christopherhahne.de)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhahnec%2Foptimizay","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhahnec%2Foptimizay","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhahnec%2Foptimizay/lists"}