{"id":22118148,"url":"https://github.com/akash1070/data-science-virtual-internship-by-anz","last_synced_at":"2025-03-24T06:18:37.071Z","repository":{"id":231695595,"uuid":"541219456","full_name":"Akash1070/Data-Science-Virtual-Internship-By-ANZ","owner":"Akash1070","description":"Exploratory data analysis and prediction of annual salary for customers from the dataset provided by ANZ.","archived":false,"fork":false,"pushed_at":"2022-09-25T15:54:08.000Z","size":3173,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-01-29T11:52:20.227Z","etag":null,"topics":["data-analysis","data-science","predictive-analytics","presentation-slides"],"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/Akash1070.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}},"created_at":"2022-09-25T15:38:06.000Z","updated_at":"2023-10-13T17:04:07.000Z","dependencies_parsed_at":"2024-04-05T11:55:35.898Z","dependency_job_id":null,"html_url":"https://github.com/Akash1070/Data-Science-Virtual-Internship-By-ANZ","commit_stats":null,"previous_names":["akash1070/data-science-virtual-internship-by-anz"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Akash1070%2FData-Science-Virtual-Internship-By-ANZ","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Akash1070%2FData-Science-Virtual-Internship-By-ANZ/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Akash1070%2FData-Science-Virtual-Internship-By-ANZ/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Akash1070%2FData-Science-Virtual-Internship-By-ANZ/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Akash1070","download_url":"https://codeload.github.com/Akash1070/Data-Science-Virtual-Internship-By-ANZ/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245217946,"owners_count":20579300,"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":["data-analysis","data-science","predictive-analytics","presentation-slides"],"created_at":"2024-12-01T13:47:59.176Z","updated_at":"2025-03-24T06:18:37.053Z","avatar_url":"https://github.com/Akash1070.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# **Data Science Virtual Internship By ANZ**\n\nRepository for all the code and reports for Data Analytics Virtual Internship Program at ANZ.\n\n\n# Project Details \n\n## Project: \n\nExploratory data analysis and prediction of annual salary for customers from the dataset provided by ANZ.\n\n## Dataset Description:\n\nThe Dataset that was given to us is based on a synthesised transaction dataset containing 3 months’ worth of transactions for 100 hypothetical customers. It contains purchases, recurring transactions, and salary transactions.\n\nThe dataset is designed to simulate realistic transaction behaviours that are observed in ANZ’s real transaction data, so many of the insights we will gather will be genuine.\n\n## Tools used:\n\n**For data wrangling and visualization:** NumPy, Pandas, Matplotlib, Seaborn\n\n**For predictive analytics:** scikit-learn\n\n**For Reporting:** Google slides\n\n## Tasks: \n\n**Task 1:** Segmenting the dataset and drawing unique insights, including visualisation of the transaction volume and assessing the effect of any outliers. \n\n**Task 2:** Exploring correlations between customer attributes, building a regression and a decision-tree prediction model based on your findings.\n\n\n## Authors\n\n- [@Akash Kumar Jha](https://github.com/Akash1070)\n\n\n## Deployment\n\n  1. Importing Necessary Libraries\n  2. Load All Datasets\n  3. Data Cleaning\n  4. Data Analysis\n  5. Predictive Analysis\n  \n## Installation\n\nTo install the libraries used in this project. Follow the \nbelow steps:\n\n```bash\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\n%matplotlib inline\nplt.style.use('ggplot')\nimport seaborn as sns\nimport warnings\nwarnings.filterwarnings('ignore')\n\nfrom sklearn.linear_model import LinearRegression\nfrom sklearn.tree import DecisionTreeRegressor\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import mean_squared_error, r2_score\n\n```\n    \n## Running Flask Api\n\nTo run tests, run the following command\n\n```bash\n  python app.py\n```\n\n## 🚀 About Me\n\nData Scientist Enthusiast | Petroleum Engineer Graduate | Solving Problems Using Data \n\n\n# Hi, I'm Akash! 👋\n\n\n## 🔗 Links\n[![github](https://img.shields.io/badge/github-000?style=for-the-badge\u0026logo=ko-fi\u0026logoColor=white)](https://github.com/Akash1070)\n[![linkedin](https://img.shields.io/badge/linkedin-0A66C2?style=for-the-badge\u0026logo=linkedin\u0026logoColor=white)](https://www.linkedin.com/in/akashkumar107/)\n\n## Tech Stack\n\n\n\n\n\n![Logo](https://businesstoys.in/assets/programs/full-stack-data-science-professional-program/tools.png)\n## Other Me\n👩‍💻 I’m interested in Petroleum Engineering\n\n🧠 I’m currently learning Data Scientist | Data Analytics | Business Analytics\n\n👯‍♀️ I’m looking to collaborate on Ideas \u0026 Data\n\n\n## 🛠 Skills\n1. Data Scientist\n2. Data Analyst\n3. Business Analyst\n4. Machine Learning \n\n\n## Future Plans \n\n⚡️ Looking forward to help drive innovations into your company as a Data Scientist\n\n⚡️ Looking forward to offer more than I take and leave the place better than i found\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fakash1070%2Fdata-science-virtual-internship-by-anz","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fakash1070%2Fdata-science-virtual-internship-by-anz","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fakash1070%2Fdata-science-virtual-internship-by-anz/lists"}