{"id":23658325,"url":"https://github.com/voorhs/ml-practice","last_synced_at":"2026-05-07T00:34:50.219Z","repository":{"id":46210756,"uuid":"416024275","full_name":"voorhs/ml-practice","owner":"voorhs","description":"ML algorithms implementation","archived":false,"fork":false,"pushed_at":"2024-01-02T01:50:23.000Z","size":32468,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-05-20T11:53:14.913Z","etag":null,"topics":["aimasters","lomonosov-msu","machine-learning","numpy","python"],"latest_commit_sha":null,"homepage":"","language":"Jupyter 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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Machine Learning Algorithms\n\nOwn implementation of machine learning algorithms:\n\n| Algorithm                                      | Code                                                         | Experiments                                                  | Report                                                       | Source                                                       |\n| ---------------------------------------------- | ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ | ------------------------------------------------------------ |\n| linear regression                              | [reg.py](https://github.com/voorhs/Machine-Learning-Algorithms/blob/main/linear-regression/reg.py) | [self-reg.ipynb](https://github.com/voorhs/Machine-Learning-Algorithms/blob/main/linear-regression/self-reg.ipynb) | —                                                            | Andrew Ng’s old course, [new one](https://www.coursera.org/learn/machine-learning?specialization=machine-learning-introduction) |\n| binary logistic regression                     | [logistic.py](https://github.com/voorhs/Machine-Learning-Algorithms/blob/main/binary-logistic-regression/logistic.py) | [self-log.ipynb](https://github.com/voorhs/Machine-Learning-Algorithms/blob/main/binary-logistic-regression/self-log.ipynb) | —                                                            | Andrew Ng’s old course, [new one](https://www.coursera.org/learn/machine-learning?specialization=machine-learning-introduction) |\n| one vs all logistic regression                 | [classification.py](https://github.com/voorhs/Machine-Learning-Algorithms/blob/main/onevsall-logistic-regression/classification.py) | [classification.ipynb](https://github.com/voorhs/Machine-Learning-Algorithms/blob/main/onevsall-logistic-regression/classification.ipynb) | —                                                            | Andrew Ng’s old course, [new one](https://www.coursera.org/learn/machine-learning?specialization=machine-learning-introduction) |\n| k-means                                        | [clust.py](https://github.com/voorhs/Machine-Learning-Algorithms/blob/main/kmeans/clust.py) | [clust.ipynb](https://github.com/voorhs/Machine-Learning-Algorithms/blob/main/kmeans/clust.ipynb) | —                                                            | [Alexander Dyakonov’s mini-course](https://github.com/Dyakonov/IML/blob/master/2020/IML2020_04cluster_01.pdf) |\n| knn                                            | [knn](https://github.com/voorhs/Machine-Learning-Algorithms/tree/main/knn/knn) | [experiments.ipynb](https://github.com/voorhs/Machine-Learning-Algorithms/blob/main/knn/experiments.ipynb) | —                                                            | [AIMasters ML course](https://github.com/voorhs/Machine-Learning-Algorithms/blob/main/knn-classification/task.pdf) |\n| SGD                                            | [sgd](https://github.com/voorhs/Machine-Learning-Algorithms/tree/main/sgd/gd) | [experiments.ipynb](https://github.com/voorhs/Machine-Learning-Algorithms/blob/main/sgd/experiments.ipynb) | [report.pdf](https://github.com/voorhs/Machine-Learning-Algorithms/blob/main/sgd/report.pdf) | [University assignment](https://github.com/mmp-practicum-team/mmp_practicum_fall_2022/blob/main/Tasks/Task%2002/task_02.pdf) |\n| decision tree                                  | [tree.ipynb](https://github.com/voorhs/Machine-Learning-Algorithms/blob/main/decision-tree/tree.ipynb) | —                                                            | —                                                            | AIMasters ML course                                          |\n| random forest and gradient boosting regression | [ensembles.py](https://github.com/voorhs/flask-ensembles/blob/main/src/ensembles.py) | [experiments.ipynb](https://github.com/voorhs/flask-ensembles/blob/main/src/experiments.ipynb) | [report.pdf](https://github.com/voorhs/flask-ensembles/blob/main/report.pdf) | [University assignment](https://github.com/mmp-practicum-team/mmp_practicum_fall_2022/blob/main/Tasks/Task%2003/task_03.pdf) |\n| GLAD (EM algo)                                 | [glad.py](https://github.com/voorhs/Machine-Learning-Algorithms/tree/main/em-glad/glad.py) | [derivation_experiments.ipynb](https://github.com/voorhs/Machine-Learning-Algorithms/tree/main/em-glad/derivation_experiments.ipynb) | —                                                            | [University assignment](https://github.com/mmp-mmro-team/-mmp_mmro_spring_2023/blob/main/homework_practice/em/homework-practice-09-em.ipynb) |\n| word alignment (EM algo)                       | [em-word-alignment](https://github.com/voorhs/Machine-Learning-Algorithms/tree/main/em-word-alignment) | [derivation_experiments.ipynb](https://github.com/voorhs/Machine-Learning-Algorithms/tree/main/em-word-alignment/derivation_experiments.ipynb) | —                                                            | [University assignment](https://github.com/mmp-mmro-team/-mmp_mmro_spring_2023/blob/main/homework_practice/em/homework-practice-09-em.ipynb) |\n| average precision subtleties                   |                                                              | [average-precision-comparison.ipynb](https://github.com/voorhs/ml-practice/blob/main/average-precision-comparision.ipynb) | —                                                            | me                                                           |\n| PCA                                            | [pca](https://github.com/voorhs/Machine-Learning-Algorithms/tree/main/pca/src.py) | [testbed.ipynb](https://github.com/voorhs/Machine-Learning-Algorithms/tree/main/pca/testbed.ipynb) | [pca](https://github.com/voorhs/Machine-Learning-Algorithms/tree/main/pca) | me                                                           |\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvoorhs%2Fml-practice","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvoorhs%2Fml-practice","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvoorhs%2Fml-practice/lists"}