{"id":20407634,"url":"https://github.com/phuijse/courses_notebooks","last_synced_at":"2025-04-12T15:21:19.559Z","repository":{"id":117592397,"uuid":"104404008","full_name":"phuijse/courses_notebooks","owner":"phuijse","description":"Jupyter notebooks for the EL4106 \"Computational Intelligence\" and AS4501 \"Astroinformatics\" courses at Universidad de Chile","archived":false,"fork":false,"pushed_at":"2017-10-31T15:02:21.000Z","size":6957,"stargazers_count":4,"open_issues_count":0,"forks_count":2,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-03-26T09:51:15.435Z","etag":null,"topics":["astroinformatics","computational-intelligence","machine-learning"],"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/phuijse.png","metadata":{"files":{"readme":"README.rst","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,"publiccode":null,"codemeta":null}},"created_at":"2017-09-21T22:13:54.000Z","updated_at":"2023-06-26T23:56:56.000Z","dependencies_parsed_at":null,"dependency_job_id":"38337844-554f-460a-b45c-034c385a5450","html_url":"https://github.com/phuijse/courses_notebooks","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/phuijse%2Fcourses_notebooks","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/phuijse%2Fcourses_notebooks/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/phuijse%2Fcourses_notebooks/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/phuijse%2Fcourses_notebooks/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/phuijse","download_url":"https://codeload.github.com/phuijse/courses_notebooks/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248586217,"owners_count":21128998,"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":["astroinformatics","computational-intelligence","machine-learning"],"created_at":"2024-11-15T05:25:31.916Z","updated_at":"2025-04-12T15:21:19.554Z","avatar_url":"https://github.com/phuijse.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"Machine-learning notebooks\n==========================\n\nJupyter notebooks on machine-learning algorithms. These are supplementary material for the AS4501 \"Astroinformatics\" and EL4106 \"Computational Intelligence\" courses at Universidad de Chile.\n\n1. `Neural networks: \u003chttp://github.com/phuijse/courses_notebooks/blob/master/notebooks/neural_nets.ipynb\u003e`_ pure-numpy multilayer perceptron (MLP), tensorflow MLP and Bayesian MLP with PyMC3\n2. `Support vector machines: \u003chttp://github.com/phuijse/courses_notebooks/blob/master/notebooks/support_vector_machines.ipynb\u003e`_ C-SVM, nu-SVM and one-class SVM using scikit-learn \n3. `Boosting with decision trees: \u003chttps://github.com/phuijse/courses_notebooks/blob/master/notebooks/decision_trees_boosting.ipynb\u003e`_ Decision trees, Adaboost and Gradient boosting using scikit-learn\n4. `Bagging with decision trees: \u003chttp://github.com/phuijse/courses_notebooks/blob/master/notebooks/neural_nets.ipynb\u003e`_ Decision trees, Bagging and Random Forest using scikit-learn\n5. `Self organizing maps: \u003chttp://github.com/phuijse/courses_notebooks/blob/master/notebooks/self-organizing-maps.ipynb\u003e`_ Color clustering through SOM using Somoclu\n\nRequirements will vary between notebooks. Incomplete list of dependecies:\n\n* Python 3 (not tested with Python 2)\n* `Numpy \u003chttp://numpy.org\u003e`_\n* `Tensorflow \u003chttp://www.tensorflow.org\u003e`_\n* `PyMC3 \u003chttp://docs.pymc.io/\u003e`_\n* `Theano \u003chttp://www.deeplearning.net/software/theano\u003e`_\n* `Scikit-learn \u003chttp://scikit-learn.org\u003e`_\n* `Somoclu \u003chttps://github.com/peterwittek/somoclu\u003e`_\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fphuijse%2Fcourses_notebooks","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fphuijse%2Fcourses_notebooks","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fphuijse%2Fcourses_notebooks/lists"}