{"id":26480523,"url":"https://github.com/mattiaferrarini/numerical-computing","last_synced_at":"2025-06-29T18:04:50.245Z","repository":{"id":221392253,"uuid":"743178226","full_name":"mattiaferrarini/Numerical-Computing","owner":"mattiaferrarini","description":"The notebooks I worked on during the Numerical Computing course, covering topics such as SVD, nonlinear equations, LSQ,  polynomial regression, unconstrained optimization and image enhancement.","archived":false,"fork":false,"pushed_at":"2024-06-18T08:17:56.000Z","size":17062,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-20T02:14:06.061Z","etag":null,"topics":["gradient-descent","image-deblurring","image-denoising","linear-systems","lsq","nonlinear-equations","regression","super-resolution","svd"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/mattiaferrarini.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null}},"created_at":"2024-01-14T15:13:37.000Z","updated_at":"2024-06-18T08:17:59.000Z","dependencies_parsed_at":"2024-02-07T18:54:44.718Z","dependency_job_id":null,"html_url":"https://github.com/mattiaferrarini/Numerical-Computing","commit_stats":null,"previous_names":["mattiaferrarini/numerical-computing"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/mattiaferrarini/Numerical-Computing","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mattiaferrarini%2FNumerical-Computing","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mattiaferrarini%2FNumerical-Computing/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mattiaferrarini%2FNumerical-Computing/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mattiaferrarini%2FNumerical-Computing/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mattiaferrarini","download_url":"https://codeload.github.com/mattiaferrarini/Numerical-Computing/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mattiaferrarini%2FNumerical-Computing/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":262642956,"owners_count":23341817,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["gradient-descent","image-deblurring","image-denoising","linear-systems","lsq","nonlinear-equations","regression","super-resolution","svd"],"created_at":"2025-03-20T02:14:22.870Z","updated_at":"2025-06-29T18:04:50.213Z","avatar_url":"https://github.com/mattiaferrarini.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Numerical Computing\nThe notebooks I worked on during the Numerical Computing course at the University of Bologna.\n\n## Topics covered\n1. **Linear systems**: matrices, norms, LU factorization, Cholesky factorization.\n2. **Singular value decomposition** with applications to **image compression**.\n3. **Linear least squares problem** and **polynomial regression**.\n4. **Nonlineare equations**: fixed-point iteration and Newton method.\n5. **Unconstrained optimization**: gradient descent and backtracking line search.\n6. **Image enhancement**: deblurring, denoising, Tikhonov regularization.\n7. **Super resolution** of images and **total variation denoising**.\n\n## Credits\nThese notebooks are a completed and modified version of the ones created by [@sedaboni](https://github.com/sedaboni) as exercises for the Numerical Computing course at the University of Bologna. \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmattiaferrarini%2Fnumerical-computing","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmattiaferrarini%2Fnumerical-computing","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmattiaferrarini%2Fnumerical-computing/lists"}