{"id":21001235,"url":"https://github.com/andrew2077/titanic-julia","last_synced_at":"2026-04-13T17:05:41.247Z","repository":{"id":187245014,"uuid":"676567580","full_name":"Andrew2077/titanic-julia","owner":"Andrew2077","description":"Deployment of AI model done with Julia on titanic dataset.","archived":false,"fork":false,"pushed_at":"2023-08-09T21:59:30.000Z","size":2211,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-20T09:46:29.438Z","etag":null,"topics":["julia","machine-learning","notebooks","randomforestclassifier"],"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/Andrew2077.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}},"created_at":"2023-08-09T13:51:38.000Z","updated_at":"2023-08-09T22:00:52.000Z","dependencies_parsed_at":"2025-01-20T09:41:59.196Z","dependency_job_id":"aa739379-5747-41b6-8891-6b0638295f6f","html_url":"https://github.com/Andrew2077/titanic-julia","commit_stats":null,"previous_names":["andrew2077/titanic-julia"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Andrew2077%2Ftitanic-julia","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Andrew2077%2Ftitanic-julia/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Andrew2077%2Ftitanic-julia/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Andrew2077%2Ftitanic-julia/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Andrew2077","download_url":"https://codeload.github.com/Andrew2077/titanic-julia/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243418755,"owners_count":20287799,"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":["julia","machine-learning","notebooks","randomforestclassifier"],"created_at":"2024-11-19T08:14:19.478Z","updated_at":"2025-12-26T17:36:04.950Z","avatar_url":"https://github.com/Andrew2077.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Titanic - Machine Learning from Disaster\n Deployment of AI model done with Julia on titanic dataset.\n## Table of Contents\n\n- [Titanic - Machine Learning from Disaster](#titanic---machine-learning-from-disaster)\n  - [Table of Contents](#table-of-contents)\n  - [Introduction](#introduction)\n    - [Librarries Used](#librarries-used)\n  - [Dataset](#dataset)\n  - [Preprocessing](#preprocessing)\n  - [Insights](#insights)\n  - [Modeling](#modeling)\n  - [Deployment](#deployment)\n  - [Results](#results)\n\n## Introduction\nEmbarked on an educational project to explore Julia for ML, utilizing Titanic dataset for preprocessing, modeling, and survival prediction.\n\n### Librarries Used \n\n- `DataFrames`: Used for handling and manipulating tabular data effectively.\n- `CSV`: Employed for reading and writing CSV files, a common data format.\n- `Plots`: Utilized for creating informative and insightful visualizations.\n- `DecisionTree`: Employed for building Random Forests machine learning model.\n\n\n## Dataset\nKaggle's Titanic ML competition introduces ML beginners to predict passenger survival \n\n[Titanic-dataset](https://www.kaggle.com/competitions/titanic)\n\n\n\n## Preprocessing\n\n\n- Managing missing data\n- Removing unnecessary features\n- Addressing categorical data\n\n## Insights\n- Death vs survival rate \n\n![](msc/survived_not_survived.png)\n\n- Death by Class\n\n![](msc/death_by_class.png)\n\n- Suvival rate by gender\n  \n![](msc/survive_by_gender.png)\n\n## Modeling\n\n\nSubsequent to data cleansing, a RandomForestClassifer was employed to construct a survival prediction model,\n\nRF hyper parameters\n\n```julia\n## set of classification parameters and respective default values\n# n_subfeatures: #*number of features to consider at random per split (default: -1, sqrt(# features))\nn_subfeatures = -1\n# n_trees: #*number of trees to train (default: 10)\nn_trees = 50\n# partial_sampling: #* fraction of samples to train each tree on (default: 0.7)\npartial_sampling = 0.7\n# max_depth: #* maximum depth of the decision trees (default: no maximum)\nmax_depth = -1\n# min_samples_leaf: #* the minimum number of samples each leaf needs to have (default: 5)\nmin_samples_leaf = 12\n# min_samples_split: #* the minimum number of samples in needed for a split (default: 2)\nmin_samples_leaf = 7\n# min_purity_increase: #* minimum purity needed for a split (default: 0.0)\nmin_samples_split = 3\nmin_purity_increase = 0.0\n# keyword rng: #* the random number generator or seed to use (default Random.GLOBAL_RNG)\nseed = 3\n## multi-threaded forests must be seeded with an `Int`\n\n```\n\n- Model achieved accuracy of `86.5%` on training data\n- model achieved accuracy of `89.7%` on test data\n\n## Deployment\nDeployed the Created model into a web application:\n`JLD2` that saves and loades new model.\n`HTTP` Connects Julia script with a frontend.\n`JSON3` To parse the inputs\n\n## Results \nSupporting the insights\n- Death occured more among females\n- Death occured more among 3d class passengers\n- Males had more chance of Survival \n  \n\nsample 1 - Female Death \n\n![](msc/female1.png)\n\nsample 2 - Male Death\n\n![](msc/male1.png)\n\nsample 3 - male Survival \n\n![](msc/male2.png)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fandrew2077%2Ftitanic-julia","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fandrew2077%2Ftitanic-julia","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fandrew2077%2Ftitanic-julia/lists"}