{"id":20983452,"url":"https://github.com/haroldeustaquio/machine-learning-projects","last_synced_at":"2025-05-14T16:32:28.720Z","repository":{"id":256787486,"uuid":"849979271","full_name":"haroldeustaquio/Machine-Learning-Projects","owner":"haroldeustaquio","description":"This repository contains Machine Learning mini-projects focused on different predictive models, from linear regression to more advanced techniques. It also includes more comprehensive end-to-end projects covering the entire ML workflow, from data preparation to model deployment.","archived":false,"fork":false,"pushed_at":"2024-10-24T11:54:32.000Z","size":99261,"stargazers_count":6,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2024-10-24T12:53:10.868Z","etag":null,"topics":["adaptive-boosting-algorithm","boosting-algorithms","boostrap-aggregating","end-to-end","machine-learning","python","ramdom-forest","regression-models","tree-classification","xgboost-algorithm","xgboost-classifier","xgboost-models","xgboost-regression"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/haroldeustaquio.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"License.txt","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":"2024-08-30T16:24:36.000Z","updated_at":"2024-10-24T11:54:36.000Z","dependencies_parsed_at":"2024-11-03T03:29:51.533Z","dependency_job_id":null,"html_url":"https://github.com/haroldeustaquio/Machine-Learning-Projects","commit_stats":null,"previous_names":["haroldeustaquio/machine-learning","haroldeustaquio/machine-learning-projects"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/haroldeustaquio%2FMachine-Learning-Projects","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/haroldeustaquio%2FMachine-Learning-Projects/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/haroldeustaquio%2FMachine-Learning-Projects/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/haroldeustaquio%2FMachine-Learning-Projects/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/haroldeustaquio","download_url":"https://codeload.github.com/haroldeustaquio/Machine-Learning-Projects/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254183159,"owners_count":22028435,"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":["adaptive-boosting-algorithm","boosting-algorithms","boostrap-aggregating","end-to-end","machine-learning","python","ramdom-forest","regression-models","tree-classification","xgboost-algorithm","xgboost-classifier","xgboost-models","xgboost-regression"],"created_at":"2024-11-19T05:48:54.190Z","updated_at":"2025-05-14T16:32:28.529Z","avatar_url":"https://github.com/haroldeustaquio.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Machine Learning Projects\n\nThis repository contains a comprehensive collection of machine learning mini-projects, covering a variety of tasks including classification, regression, clustering, dimensionality reduction, and sentiment analysis. Each category demonstrates the application of specific machine learning techniques to solve real-world problems, providing a practical introduction to various models and methodologies.\n\n---\n\n## Repository Structure\n\nThe projects are organized into the following main categories:\n\n1. **Linear Regression**  \n   Regression projects applying linear regression techniques to various datasets. [See more](https://github.com/haroldeustaquio/Machine-Learning-Projects/tree/main/Linear-Regression)  \n\n   - **Projects**:\n     - Beer Consumption Prediction  \n     - Personal Insurance Cost Prediction  \n     - Water Temperature Prediction Using Oceanographic Data  \n     - Weather Prediction During World War II  \n     - Weather Prediction in Szeged (2006-2016)  \n\n2. **Logistic Regression**  \n   Classification projects focused on logistic regression models. [See more](https://github.com/haroldeustaquio/Machine-Learning-Projects/tree/main/Logistic-Regression)  \n\n   - **Projects**:\n     - Fake Bills Detector  \n     - Halloween Candy Power Ranking  \n     - Heart Disease Prediction  \n     - Predicting MBTI Personality Types  \n     - Titanic Survival Prediction  \n\n3. **Naive Bayes**  \n   Sentiment analysis projects applying Naive Bayes models to classify text data. [See more](https://github.com/haroldeustaquio/Machine-Learning-Projects/tree/main/Naive-Bayes)  \n\n   - **Projects**:\n     - Sentiment Analysis of Airline Tweets  \n     - Sentiment Classification on 1,600,000 Tweets  \n\n4. **Trees and Ensemble**  \n   Projects using decision trees and ensemble models for both classification and regression tasks.  [See more](https://github.com/haroldeustaquio/Machine-Learning-Projects/tree/main/Trees_and_Ensemble)\n\n   - **Classification**: Projects using decision trees and ensemble models to classify datasets. [See more](https://github.com/haroldeustaquio/Machine-Learning-Projects/tree/main/Trees_and_Ensemble/Classification)  \n\n     - **Projects**:\n       - Basic Classification with Synthetic Data  \n       - Cirrhosis Patient Survival Prediction  \n\n   - **Regression**: Projects using decision trees and ensemble models for regression tasks. [See more](https://github.com/haroldeustaquio/Machine-Learning-Projects/tree/main/Trees_and_Ensemble/Regression)  \n\n     - **Projects**:\n       - Car Price Prediction  \n       - Boston Housing Price Prediction  \n\n5. **Clustering and Dimensionality Reduction**  \n   Projects focusing on clustering and dimensionality reduction techniques, such as K-Means and PCA. [See more](https://github.com/haroldeustaquio/Machine-Learning-Projects/tree/main/Clustering-DimReduction)  \n\n   - **Projects**:\n     - Breast Cancer Wisconsin Diagnostic Clustering using PCA  \n     - Clustering on the Iris Dataset  \n\nEach subfolder contains a detailed README with project descriptions, dataset information, and specific results.\n\n---\nFeel free to explore each project to understand the methodologies and results in more detail!\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fharoldeustaquio%2Fmachine-learning-projects","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fharoldeustaquio%2Fmachine-learning-projects","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fharoldeustaquio%2Fmachine-learning-projects/lists"}