{"id":26201713,"url":"https://github.com/abbaszaidi123/product-demand-forecasting-using-ml","last_synced_at":"2025-12-24T09:18:06.777Z","repository":{"id":281732669,"uuid":"946246625","full_name":"abbaszaidi123/Product-Demand-Forecasting-Using-ML","owner":"abbaszaidi123","description":null,"archived":false,"fork":false,"pushed_at":"2025-03-10T20:59:16.000Z","size":0,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-10T21:35:53.975Z","etag":null,"topics":["ai","mlops","python","testing","training"],"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/abbaszaidi123.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":"2025-03-10T20:58:24.000Z","updated_at":"2025-03-10T20:59:45.000Z","dependencies_parsed_at":"2025-03-10T21:35:56.937Z","dependency_job_id":"832964ae-6631-4150-8e45-1ed776f5f39e","html_url":"https://github.com/abbaszaidi123/Product-Demand-Forecasting-Using-ML","commit_stats":null,"previous_names":["abbaszaidi123/product-demand-forecasting-using-ml"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abbaszaidi123%2FProduct-Demand-Forecasting-Using-ML","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abbaszaidi123%2FProduct-Demand-Forecasting-Using-ML/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abbaszaidi123%2FProduct-Demand-Forecasting-Using-ML/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/abbaszaidi123%2FProduct-Demand-Forecasting-Using-ML/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/abbaszaidi123","download_url":"https://codeload.github.com/abbaszaidi123/Product-Demand-Forecasting-Using-ML/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243148101,"owners_count":20243917,"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":["ai","mlops","python","testing","training"],"created_at":"2025-03-12T03:23:24.700Z","updated_at":"2025-12-24T09:18:06.765Z","avatar_url":"https://github.com/abbaszaidi123.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Demand Forecasting using Machine Learning\r\n\r\n\r\nDemand forecasting is the process of making estimations about future customer demand over a defined period, using historical data and other information. \r\n\r\nUsually organisations follow tranditional forecasting techniques/algorithms such as Auto Arima, Auto Arima, Sarima, Simple moving average and many more.\r\n\r\n## Table of Contents\r\n\r\n- [Goal](#goal)\r\n- [Workflow](#workflow)\r\n- [Required Packages](#require)\r\n\r\n\r\n## Goal \u003ca name = \"goal\"\u003e\u003c/a\u003e\r\n\r\nDue to the recent boost in AI world, companies have started researching the possibility of using machine learning in place of tranditional approach.\r\n\r\nTuning traditional algorithms takes a significant amount of effords and domain expertise as well. \r\n\r\nIn this repo, we are trying to figure out a way of predict the same using machine learning algorithms. \r\n\r\n\r\n## Data \u003ca name = \"dataset\"\u003e\u003c/a\u003e\r\n\r\nThe dataset comprised of units sold on a daily basis along with details regarding the sales, eg. SKU(product id), Store, price etc.\r\n\r\n*record_ID,\tweek,\tstore_id,\tsku_id,\ttotal_price,\tbase_price,\tis_featured_sku,\tis_display_sku,\tunits_sold*\r\n\r\n\r\n## Workflow \u003ca name = \"workflow\"\u003e\u003c/a\u003e\r\n\r\n- Handling missing values\r\n- Feature selection based on my previous experience in Supply chain domain\r\n- Converting dataset into time series format to apply supervised learning approach.\r\n- Regression Modeling\r\n  - Random Forest\r\n  - XGBoost\r\n  - SVM (future scope)\r\n- Hyperparameter Tuning\r\n\r\n## Result\r\n![train](https://github.com/shreyas-jk/Demand-Forecasting-Using-ML/blob/main/final.png?raw=true)\r\n\r\n\r\n\r\n## Required Packages \u003ca name = \"require\"\u003e\u003c/a\u003e\r\n\r\n- numpy\r\n- pandas\r\n- sklearn\r\n- easypreprocessing \r\n- seaborn \r\n- matplotlib\r\n- xgboost\r\n\r\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabbaszaidi123%2Fproduct-demand-forecasting-using-ml","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fabbaszaidi123%2Fproduct-demand-forecasting-using-ml","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fabbaszaidi123%2Fproduct-demand-forecasting-using-ml/lists"}