{"id":18809523,"url":"https://github.com/rfsantacruz/ml-nb","last_synced_at":"2026-05-20T05:02:36.269Z","repository":{"id":83820303,"uuid":"89581483","full_name":"rfsantacruz/ml-nb","owner":"rfsantacruz","description":"IPython Notebooks of machine learning algorithms and applications","archived":false,"fork":false,"pushed_at":"2017-04-27T10:44:01.000Z","size":318,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-05-22T02:40:58.002Z","etag":null,"topics":["data-science","machine-learning","machine-vision","python"],"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/rfsantacruz.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,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2017-04-27T09:39:22.000Z","updated_at":"2017-09-17T04:02:04.000Z","dependencies_parsed_at":null,"dependency_job_id":"590208a0-9911-42d4-b666-106a59cbcb53","html_url":"https://github.com/rfsantacruz/ml-nb","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/rfsantacruz/ml-nb","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rfsantacruz%2Fml-nb","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rfsantacruz%2Fml-nb/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rfsantacruz%2Fml-nb/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rfsantacruz%2Fml-nb/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/rfsantacruz","download_url":"https://codeload.github.com/rfsantacruz/ml-nb/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rfsantacruz%2Fml-nb/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":278672983,"owners_count":26026010,"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","status":"online","status_checked_at":"2025-10-06T02:00:05.630Z","response_time":65,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"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":["data-science","machine-learning","machine-vision","python"],"created_at":"2024-11-07T23:16:40.392Z","updated_at":"2025-10-06T20:25:24.248Z","avatar_url":"https://github.com/rfsantacruz.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# ml-nb: Machine Learning Notebook\nThis repository contains a set of IPython Notebooks about machine learning algorithms and its applications. Some of the content is based on the [PRML Book](https://www.microsoft.com/en-us/research/people/cmbishop/?from=http%3A%2F%2Fresearch.microsoft.com%2F%7Ecmbishop%2Fprml%2Findex.htm) by Christopher Bishop.\n\n## Requirements:\nThe notebooks are developed with:\n* Python 3\n* Numpy\n* SciPy\n* Pandas\n\nThese libraries can be easily installed using Anaconda and Pip.\n\n## Notebooks\n1. [Parametric Density Estimation](./ParametricDensityEstimation.ipynb): Estimating a parametric density distributions.\n2. [Nonparametric Density Estimation](./NonparametricDensityEstimation.ipynb): How about non-parametric density estimation.\n3. [Linear Regression Models](./LinearRegressionModels.ipynb): Classic linear models for regression in a toy data.\n4. [Linear Classification Models](./LinearClassificationModels.ipynb): Linear classification models applied to multi-class classification.\n5. [Neural Networks](./NeuralNetworks.ipynb): Exploring non-linearity with Neural networks.\n6. [Kernel Trick](./KernelTrick.ipynb): Applying the kernel trink on regression models.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frfsantacruz%2Fml-nb","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frfsantacruz%2Fml-nb","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frfsantacruz%2Fml-nb/lists"}