linuxto5re / salesandguestmanagementmldotnet

welcome to our Sales and Guest Projection repository! Discover precise guest predictions via ML.NET, historical data, and advanced tech. This model also applies to sales forecasts, fueled by ML.NET's capabilities. In addition, we've added data visualization.

Guest and Sales Projection/Visualization Using Machine Learning in C# (ML.NET)

Welcome to the Sales and Guest Projection project repository!

• Explore the Sales and Guest Projection repository, utilizing ML.NET, C#, MVVM, Microsoft SQL Server and WPF.
• Predict future guests using advanced tech - historical data fuels projections for upcoming days.
• Tap into past actual and projected guests for accurate guest forecasts, a powerful business tool.
• The same logic can be applied for future sales projections using machine learning with the help of ML.NET.
• In bonus, take a look of data visualization where we've used Line chart and bar graph.

Projected Results

Projection - 1:


Projection - 2:

Visualization Sample

Columns Definition

• Time : Column used to describe the timestamp for guest count.
• Guest Count : Actual guest count for the specified timestamp.
• Projected MyStore : Projected guest count using the Average algorithm in the existing application.
• Projected ML : Projected guest count using machine learning (ML.NET).
• Difference ML : Guest Count - Projected ML
• Difference SDM : Guest Count - Projected MyStore

Technologies Used

• ML.NET
• OxyPlot (Data Visualization)
• C#
• MVVM (Model-View-ViewModel)
• Microsoft SQL Server Management (SSMS)
• WPF (Windows Presentation Foundation)

Getting Started

Follow these steps to set up the project in Visual Studio:

Requirements

• Visual Studio (Any version is compatible)
• Microsoft SQL Server
• .NET 5.0*

1. Clone or download the project repository to your local machine.

git clone https://github.com/LinUxTo5re/SalesAndGuestManagementMLdotnet.git

2. Open Microsoft SQL Server and set up a database. Execute the stored procedure provided in the ML_POC.sql file.
3. If you don't have access to our database, it's recommended to create your own SQL/NoSQL database and modify the code and queries according to your needs.
4. Unzip or open the downloaded folder or go to cloned directory in your system and double-click on HourlySalesReport.sln to open the project in Visual Studio.
5. Make a configuration adjustment: Search for settings.settings in the Solution Explorer's search bar and open settings.settings.
6. In the settings.settings page, locate the data source setting and update it with your server's name as demonstrated in Screenshot-3. Save the changes and close the settings.settings page.
7. Run the application and enjoy the code.

Set Up SSMS Instance and Update settings.settings:

Screenshot-1:


Screenshot-2:


Screenshot-3:

Contributors

• Aadarsh Tiwari: https://github.com/aadarsh0001

Licensed under GNU