{"id":21597800,"url":"https://github.com/priyanshu501/data_science_practice","last_synced_at":"2026-05-17T21:01:47.804Z","repository":{"id":240555006,"uuid":"791466959","full_name":"Priyanshu501/Data_Science_Practice","owner":"Priyanshu501","description":"Practice Assignments for Data Science Coursework","archived":false,"fork":false,"pushed_at":"2024-05-23T15:25:49.000Z","size":33342,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-24T17:45:41.242Z","etag":null,"topics":["association-rules","boosting-algorithms","clustering","decision-tree","exploratory-data-analysis","hypothesis-testing","knn","logistic-regression","multiple-linear-regression","neural-networks","nlp","principal-component-analysis","python","random-forest","recommendation-system","statistics","support-vector-machines","timeseries-analysis"],"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/Priyanshu501.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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":"2024-04-24T19:14:27.000Z","updated_at":"2024-07-18T20:03:02.000Z","dependencies_parsed_at":"2025-01-24T17:53:15.873Z","dependency_job_id":null,"html_url":"https://github.com/Priyanshu501/Data_Science_Practice","commit_stats":null,"previous_names":["priyanshu501/assignments"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Priyanshu501%2FData_Science_Practice","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Priyanshu501%2FData_Science_Practice/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Priyanshu501%2FData_Science_Practice/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Priyanshu501%2FData_Science_Practice/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Priyanshu501","download_url":"https://codeload.github.com/Priyanshu501/Data_Science_Practice/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244210054,"owners_count":20416393,"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":["association-rules","boosting-algorithms","clustering","decision-tree","exploratory-data-analysis","hypothesis-testing","knn","logistic-regression","multiple-linear-regression","neural-networks","nlp","principal-component-analysis","python","random-forest","recommendation-system","statistics","support-vector-machines","timeseries-analysis"],"created_at":"2024-11-24T18:10:01.349Z","updated_at":"2026-05-17T21:01:47.725Z","avatar_url":"https://github.com/Priyanshu501.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Data Science: Practice Repository\n\nWelcome to the repository for my Data Science Assignments! This repository contains all the assignments I have completed as part of my data science coursework. Each assignment is organized into its own folder, containing the relevant files, code, and documentation.\n\n### Repository Structure\n\nThe repository is organized by assignment, with each assignment in its own directory. The structure is as follows:\n\n\u003cpre\u003e\n.\n├── Assignment1/\n│   ├── problem_statement.docx or .txt\n│   ├── assignment1.ipynb\n│   ├── data.csv or .xlsx\n├── Assignment2/\n│   ├── problem_statement.docx or .txt\n│   ├── assignment2.ipynb\n│   ├── data.csv or .xlsx\n├── Assignment3/\n│   ├── problem_statement.docx or .txt\n│   ├── assignment2.ipynb\n│   ├── data.csv or .xlsx\n├── README.md\n└── LICENSE\n\u003c/pre\u003e\n\n## Assignments\n\nEach assignment folder contains the following:\n\n* `problem_statement.docx`: A brief description of the assignment, the tasks involved, and any specific instructions or notes.\n\n* `assignmentX.ipynb`: The Jupyter Notebook file with the code and explanations for the assignment tasks.\n\n* `data.csv`: Dataset for the assignment\n\n## Problem Statement Structure\n\n* Tasks:\n\n    1. Data Cleaning and Preprocessing\n\n        * Loading and exploring the dataset.\n        * Handling missing values.\n        * Data normalization and transformation.\n\n    2. Exploratory Data Analysis (EDA)\n\n        * Performing descriptive statistics.\n        * Visualizing data distributions and relationships.\n        * Identifying patterns and outliers.\n    \n    3. Machine Learning Model Development\n\n        * Splitting data into training and test sets.\n        * Training and Evaluating different machine learning models.\n        * Hyperparameter tuning and model selection\n\n    ... ... ...\n\n## How to Use\n\n1. Clone the repository to your local machine:\n\n\u003cpre\u003e\ngit clone https://github.com/Priyanshu501/Data_Science_Practice.git\n\u003c/pre\u003e\n\n2. Navigate to the assignment directory you are interested in:\n\n\u003cpre\u003e\ncd Data_Science_Practice/`assignment`\n\u003c/pre\u003e\n\n3. Open the Jupyter Notebook for the assignment:\n\n\u003cpre\u003e\njupyter notebook `assignment.ipynb`\n\u003c/pre\u003e\n\n4. Follow the instructions in the notebook to run the code and review the results.\n\n## Contributing\n\nThis repository is intended for educational purposes, and contributions are not expected. However, if you have suggestions or find any issues, please feel free to open an issue or submit a pull request.\n\n## License\n\nThis repository is licensed under the MIT License. See the `LICENSE` file for more information.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpriyanshu501%2Fdata_science_practice","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpriyanshu501%2Fdata_science_practice","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpriyanshu501%2Fdata_science_practice/lists"}