https://github.com/dimits-ts/numerical-optimization

Using Constrained LS, SVD analysis and PageRank to efficiently solve common problems
https://github.com/dimits-ts/numerical-optimization

constrained-optimization linear-algebra pagerank power-method svd-factorization

Last synced: about 8 hours ago
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Using Constrained LS, SVD analysis and PageRank to efficiently solve common problems

• Host: GitHub
• URL: https://github.com/dimits-ts/numerical-optimization
• Owner: dimits-ts
• Created: 2024-02-20T13:38:01.000Z (9 months ago)
• Default Branch: master
• Last Pushed: 2024-03-31T10:01:12.000Z (7 months ago)
• Last Synced: 2024-04-22T02:45:10.083Z (7 months ago)
• Topics: constrained-optimization, linear-algebra, pagerank, power-method, svd-factorization
• Language: Jupyter Notebook
• Homepage:
• Size: 51.4 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Numerical Optimization and Linear Algebra

This repository houses 4 distinct projects:

* [House price prediction](https://github.com/dimits-exe/numerical-optimization/tree/master/assign-1)

* [Optimal light placement for rooms using Constrained Linear Squares](https://github.com/dimits-exe/numerical-optimization/tree/master/assign-2)

* [Digit classification using a custpom SVD classifier](https://github.com/dimits-exe/numerical-optimization/tree/master/assign-3)

* [PageRank implementation (power method & system solution) with exploit examples](https://github.com/dimits-exe/numerical-optimization/tree/master/assign-4)

Each of these projects (aside from the 1st) features a full typed report in LaTEX as well as the source code in one or more Python files.