{"id":18351488,"url":"https://github.com/saikat-roy/uni-bonn-pattern-recognition","last_synced_at":"2026-04-25T12:36:43.879Z","repository":{"id":84255017,"uuid":"180897608","full_name":"saikat-roy/Uni-Bonn-Pattern-Recognition","owner":"saikat-roy","description":"Code from the Pattern Recognition (1) at University of Bonn (SS 19): Normal Distribution fitting, MLE, Fractal Dimensions, Bayesian Regression NN, kDTrees, k-mean \u0026 spectral clustering, PCA, LDA","archived":false,"fork":false,"pushed_at":"2019-11-16T08:21:51.000Z","size":7242,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":6,"default_branch":"master","last_synced_at":"2026-04-25T12:36:42.303Z","etag":null,"topics":["bonn","lecture","machine-learning","pattern-recognition","python3","university","visualization"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/saikat-roy.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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,"publiccode":null,"codemeta":null}},"created_at":"2019-04-12T00:13:09.000Z","updated_at":"2021-07-25T19:49:57.000Z","dependencies_parsed_at":"2023-03-12T22:12:52.621Z","dependency_job_id":null,"html_url":"https://github.com/saikat-roy/Uni-Bonn-Pattern-Recognition","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/saikat-roy/Uni-Bonn-Pattern-Recognition","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saikat-roy%2FUni-Bonn-Pattern-Recognition","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saikat-roy%2FUni-Bonn-Pattern-Recognition/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saikat-roy%2FUni-Bonn-Pattern-Recognition/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saikat-roy%2FUni-Bonn-Pattern-Recognition/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/saikat-roy","download_url":"https://codeload.github.com/saikat-roy/Uni-Bonn-Pattern-Recognition/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saikat-roy%2FUni-Bonn-Pattern-Recognition/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32262801,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-25T09:15:33.318Z","status":"ssl_error","status_checked_at":"2026-04-25T09:15:31.997Z","response_time":59,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":["bonn","lecture","machine-learning","pattern-recognition","python3","university","visualization"],"created_at":"2024-11-05T21:31:29.641Z","updated_at":"2026-04-25T12:36:43.860Z","avatar_url":"https://github.com/saikat-roy.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# University of Bonn: Pattern Recognition (1) SS 2019\nCode from the Pattern Recognition (1) lecture at University of Bonn (SS19). A lot of algorithms were implemented in Python during the lecture without the usage of libraries like scikit-learn (atleast too often). The focus during coding was vectorized implementations instead of the heavy use of iterations.\n\nThe practical part of the lecture consisted of 3 projects which involved the implementation of a breadth of machine learning and pattern recognition algorithms.\n\n## Project 1\n1. [Matplotlib visualization of 1D data](https://github.com/saikat-roy/Uni-Bonn-Pattern-Recognition/tree/master/Project1/task1_1)\n2. [Fitting 1D Gaussian distribution to data](https://github.com/saikat-roy/Uni-Bonn-Pattern-Recognition/tree/master/Project1/task1_2)\n3. [Maximum likelihood estimate of Weibull Distribution](https://github.com/saikat-roy/Uni-Bonn-Pattern-Recognition/tree/master/Project1/task1_3)\n4. [Drawing unit circles with different distance metrics](https://github.com/saikat-roy/Uni-Bonn-Pattern-Recognition/tree/master/Project1/task1_4)\n5. [Estimating dimensions of Fractal objects in an image](https://github.com/saikat-roy/Uni-Bonn-Pattern-Recognition/tree/master/Project1/task1_5)\n\n## Project 2\n1. [Least Squares Regression for missing value prediction](https://github.com/saikat-roy/Uni-Bonn-Pattern-Recognition/tree/master/Project2/task2_1)\n2. [Conditional Expectation for missing value prediction](https://github.com/saikat-roy/Uni-Bonn-Pattern-Recognition/tree/master/Project2/task2_2)\n3. [Bayesian regression for missing value prediction](https://github.com/saikat-roy/Uni-Bonn-Pattern-Recognition/tree/master/Project2/task2_3)\n4. [Boolean functions and boolean Fourier transform](https://github.com/saikat-roy/Uni-Bonn-Pattern-Recognition/tree/master/Project2/task2_4_1)\n5. [Nearest neighbour classifier](https://github.com/saikat-roy/Uni-Bonn-Pattern-Recognition/tree/master/Project2/task2_4_2)\n6. [Nearest neighbour search using KD-Trees](https://github.com/saikat-roy/Uni-Bonn-Pattern-Recognition/tree/master/Project2/task2_5)\n\n## Project 3\n1. [k-means clustering](https://github.com/saikat-roy/Uni-Bonn-Pattern-Recognition/tree/master/Project2/Task3_1)\n2. [Spectral clustering](https://github.com/saikat-roy/Uni-Bonn-Pattern-Recognition/tree/master/Project2/Task3_2)\n3. [Dimensionality reduction using PCA and multiclass-LDA](https://github.com/saikat-roy/Uni-Bonn-Pattern-Recognition/tree/master/Project2/Task3_3)\n4. [Non-monotonous activation units for XOR problem using a single neuron](https://github.com/saikat-roy/Uni-Bonn-Pattern-Recognition/tree/master/Project2/Task3_4)\n5. [Exploring numerical instabilities with polynomial regression and normalization techniques](https://github.com/saikat-roy/Uni-Bonn-Pattern-Recognition/tree/master/Project3/Task3_5_saikatroy)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsaikat-roy%2Funi-bonn-pattern-recognition","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsaikat-roy%2Funi-bonn-pattern-recognition","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsaikat-roy%2Funi-bonn-pattern-recognition/lists"}