https://github.com/sayamalt/superstore-sales-prediction

Successfully established a machine learning model that can accurately predict the sales of a superstore based on various features such as quantity, profit, discount, postal code, etc. The features are mainly associated with order details and customer demographics.
https://github.com/sayamalt/superstore-sales-prediction

azure-machine-learning azure-web-app-service cicd-deployment cross-validation data-cleaning-and-preprocessing data-visualization exploratory-data-analysis feature-engineering github-actions-ci-cd hyperparameter-tuning machine-learning model-deployment model-retraining model-testing model-training-and-evaluation regression-models

Last synced: about 17 hours ago
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Successfully established a machine learning model that can accurately predict the sales of a superstore based on various features such as quantity, profit, discount, postal code, etc. The features are mainly associated with order details and customer demographics.

• Host: GitHub
• URL: https://github.com/sayamalt/superstore-sales-prediction
• Owner: SayamAlt
• License: apache-2.0
• Created: 2024-02-03T19:52:49.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2024-02-11T06:09:52.000Z (9 months ago)
• Last Synced: 2024-02-12T04:21:33.706Z (9 months ago)
• Topics: azure-machine-learning, azure-web-app-service, cicd-deployment, cross-validation, data-cleaning-and-preprocessing, data-visualization, exploratory-data-analysis, feature-engineering, github-actions-ci-cd, hyperparameter-tuning, machine-learning, model-deployment, model-retraining, model-testing, model-training-and-evaluation, regression-models
• Language: Jupyter Notebook
• Homepage: https://superstore-sales-prediction.azurewebsites.net/
• Size: 35.5 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
## About Dataset

![Superstore Sales](https://img.nbc.com/sites/nbcunbc/files/images/2020/9/30/Superstore-S6-Logo-1920x1080.jpg)

![Superstore](https://live.staticflickr.com/6088/6075050600_ab3c24a0fb_b.jpg)

![Superstore](https://i.pinimg.com/originals/2b/ec/b8/2becb88220bd64717620289228b9e099.jpg)

The "Superstore Sales" dataset is a comprehensive and versatile collection of data that provides valuable insights into sales, customer behavior, and product performance. This dataset offers a rich resource for in-depth analysis.

Containing information from diverse regions and segments, the dataset enables exploration of trends, patterns, and correlations in sales and customer preferences. The dataset encompasses sales transactions, enabling researchers and analysts to understand buying patterns, identify high-demand products, and assess the effectiveness of different shipping modes.

Moreover, the dataset provides an opportunity to examine the impact of various factors such as discounts, geographical locations, and product categories on profitability. By analyzing this dataset, businesses and data enthusiasts can uncover actionable insights for optimizing pricing strategies, supply chain management, and customer engagement.

Whether used for educational purposes, business strategy formulation, or data analysis practice, the "Superstore Sales" dataset offers a comprehensive platform to delve into the dynamics of sales operations, customer interactions, and the factors that drive business success.