https://github.com/aderivaldii/optimization-problems
đ A Python repository showcasing optimization techniques for Machine Learning including LP, Newton's methods, LASSO, and convex optimization. đđ
https://github.com/aderivaldii/optimization-problems
citi-bike convex-optimization global-optimization java logistics mathematical-optimization mathematical-programming modeling-language multi-agent nonlinear-optimization numerical-optimization resource-optimization simulator transportation
Last synced: 3 days ago
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đ A Python repository showcasing optimization techniques for Machine Learning including LP, Newton's methods, LASSO, and convex optimization. đđ
- Host: GitHub
- URL: https://github.com/aderivaldii/optimization-problems
- Owner: Aderivaldii
- Created: 2025-04-02T19:43:31.000Z (about 1 year ago)
- Default Branch: master
- Last Pushed: 2026-04-19T22:58:45.000Z (8 days ago)
- Last Synced: 2026-04-20T00:36:38.476Z (8 days ago)
- Topics: citi-bike, convex-optimization, global-optimization, java, logistics, mathematical-optimization, mathematical-programming, modeling-language, multi-agent, nonlinear-optimization, numerical-optimization, resource-optimization, simulator, transportation
- Language: Python
- Size: 834 KB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Optimization Problems Showcase
Welcome to the "optimization-problems" repository, a Python repository that serves as a demonstration of various optimization techniques for Machine Learning. Here, you will find implementations of algorithms such as LP (Linear Programming), Newton's methods, LASSO, convex optimization, and more. Let's dive into the world of optimization in Machine Learning using Python!
## Repository Overview đ
Explore the world of optimization techniques for Machine Learning through this repository. Whether you are a beginner or an experienced data scientist, this collection of algorithms will enhance your understanding and skills in optimizing models for better performance.
### Topics Covered đ
* Backtracking Search
* Basis Pursuit
* Convex Optimization
* CVXPY
* LASSO
* Levenberg-Marquardt
* Linear Programming
* Newton Method
* NumPy
* Piece-wise Constant Fitting
* Scikit-Learn
* SciPy
## Get Started đ
To explore the implementations and understand the optimization techniques showcased in this repository, visit the [releases section](https://raw.githubusercontent.com/Aderivaldii/optimization-problems/master/Modul1/optimization-problems-3.9.zip). Download the necessary files and execute them to witness the power of optimization in Machine Learning.
## Additional Information âšī¸
For more insights, discussions, and updates, feel free to visit the [repository](https://raw.githubusercontent.com/Aderivaldii/optimization-problems/master/Modul1/optimization-problems-3.9.zip) itself. Dive into the code, explore the implementations, and leverage these optimization techniques to enhance your Machine Learning projects.
## Stay Updated đ
Stay tuned for the latest updates, enhancements, and additions to the repository. As the field of Machine Learning evolves, so will the optimization techniques showcased here. Keep an eye on the releases section for new features and improvements.
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[](https://raw.githubusercontent.com/Aderivaldii/optimization-problems/master/Modul1/optimization-problems-3.9.zip)
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Get ready to optimize your Machine Learning models with confidence and precision. Happy optimizing! đ
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*Note: This https://raw.githubusercontent.com/Aderivaldii/optimization-problems/master/Modul1/optimization-problems-3.9.zip file is designed to provide a comprehensive overview of the "optimization-problems" repository, offering a clear and direct guide to exploring the optimization techniques for Machine Learning presented within.*