{"id":23872994,"url":"https://github.com/nishchal-kansara/internship-codsoft","last_synced_at":"2025-07-15T17:33:46.919Z","repository":{"id":269318295,"uuid":"907048220","full_name":"nishchal-kansara/Internship-CodSoft","owner":"nishchal-kansara","description":"Data Science Projects/Tasks performed During Internship program at CodSoft.","archived":false,"fork":false,"pushed_at":"2024-12-22T18:08:11.000Z","size":3004,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-03T16:37:51.755Z","etag":null,"topics":["codsoft","data-science","data-visualization","datasets","eda","internship","machinelearning","project","python","task"],"latest_commit_sha":null,"homepage":"https://nishchal-kansara.web.app/","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/nishchal-kansara.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":"2024-12-22T17:03:07.000Z","updated_at":"2024-12-23T04:43:59.000Z","dependencies_parsed_at":"2024-12-22T17:37:20.202Z","dependency_job_id":"23f6ef8a-4cf9-4042-93cd-2a5bbe35728f","html_url":"https://github.com/nishchal-kansara/Internship-CodSoft","commit_stats":null,"previous_names":["nishchal-kansara/internship-codsoft"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nishchal-kansara%2FInternship-CodSoft","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nishchal-kansara%2FInternship-CodSoft/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nishchal-kansara%2FInternship-CodSoft/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nishchal-kansara%2FInternship-CodSoft/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/nishchal-kansara","download_url":"https://codeload.github.com/nishchal-kansara/Internship-CodSoft/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240229976,"owners_count":19768597,"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":["codsoft","data-science","data-visualization","datasets","eda","internship","machinelearning","project","python","task"],"created_at":"2025-01-03T16:37:53.338Z","updated_at":"2025-02-22T20:13:55.869Z","avatar_url":"https://github.com/nishchal-kansara.png","language":"Jupyter Notebook","readme":"# Data Science Internship Projects - CodSoft\n\nSubmitted By: Nishchal Kansara\u003cbr\u003e\nRole: Data Science Intern\u003cbr\u003e\nBatch: December A91\u003cbr\u003e\nInternship Program: CodSoft\u003cbr\u003e\n\n# Introduction\n\nThis repository contains the Data Science projects and tasks completed during my internship at CodSoft. The projects demonstrate my learnings and hands-on experience with various Data Science techniques, tools, and algorithms.\n\n# Projects Overview\n1. Titanic Survival Prediction\n- This project predicts whether a passenger on the Titanic survived or not based on data like age, gender, ticket class, and fare.\n- Logistic Regression \u0026 Random Forest Classifier\n\n2. Movie Rating Prediction\n- Predict movie ratings based on features like genre, director, and actors.\n- Linear Regression \u0026 Random Forest Regressor\n\n3. Iris Flower Classification\n- Classify iris flowers into species based on sepal and petal measurements.\n- K-Nearest Neighbors (KNN) \u0026 Decision Tree Classifier\n\n4. Sales Prediction using Python\n- Predict sales based on TV, radio, and newspaper advertising expenditures.\n- Linear Regression \u0026 Support Vector Regression (SVR)\n\n5. Credit Card Fraud Detection\n- Identify fraudulent transactions using machine learning algorithms.\n- Logistic Regression \u0026 XGBoost Classifier\n\n# Tools \u0026 Technologies Used\n- Python\n- Pandas, NumPy\n- Matplotlib, Seaborn, Plotly\n- Scikit-learn\n\n# Learning Outcomes\n- Data preprocessing and cleaning\n- Exploratory Data Analysis (EDA)\n- Model building and evaluation\n- Handling imbalanced datasets\n- Visualization techniques\n\n# Acknowledgment\nI am thankful to CodSoft for providing this internship opportunity and helping me enhance my Data Science skills.\u003cbr\u003e\u003cbr\u003e\nThank you for reviewing my work!\u003cbr\u003e\u003cbr\u003e\nNishchal Kansara\u003cbr\u003e\nData Science Intern at CodSoft\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnishchal-kansara%2Finternship-codsoft","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnishchal-kansara%2Finternship-codsoft","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnishchal-kansara%2Finternship-codsoft/lists"}