Atenxion AI PlatformLearn how our product works
Atenxion Platform

Step 1: Import Your Data

When creating a new train data entry, select your preferred engine tab: RunPod or BigQuery TabFM.

  • Select Platform Tab: Choose between RunPod at the top of the interface.
  • Selecting a Data Source

When creating a new predictive train data entry using RunPod, you can choose between two primary data source options from the Data source dropdown:

  1. Database Connection
  2. Upload File
Figure: runpod data source
Figure: runpod data source

Option 1: Database Connection

Connect directly to your database server for real-time data access.

  • Database: Select your database type from the dropdown (e.g., PostgreSQL).
  • Domain: Enter your database server domain or host address.
  • Port: Specify the connection port number.
  • Database Name: Enter the name of the target database.
  • Username: Provide your database authentication username.
  • Password: Enter your database password.
  • Table Name: Specify the specific table containing the training dataset.
Figure: RunPod database connection setup screen showing form fields for Database, Domain, Port, Database Name, Username, Password, and Table Name.
Figure: RunPod database connection interface for configuring data source parameters.


Option 2: Upload File

Upload your structured spreadsheet or data file directly to the platform.

  • Upload via File: Add structured data by uploading files.

  • Methods:

    • Drag and drop your file directly into the designated upload box.

    • Click Browse files to select a file from your local storage.

  • Supported File Types: .csv, .xlsx.

Figure: runpod upload file
Figure: runpod upload file


Step 2: Configure Model Settings

Before completing the setup, configure the predictive task type and target prediction column

Figure: Task Settings modal pop-up on top of the RunPod configuration screen highlighting Task Type and Target Column fields.
Figure: Task Settings modal for defining model task type and target column.
  • Click the Model Settings button in the top right corner of the dashboard.
  • In the Task Settings modal:
    • Task Type: Open the dropdown and select either Classification or Regression.
    • Target Column: Enter the specific column name from your dataset that you want the model to predict.
Figure: Selecting model task type (Classification or Regression) in Task Settings.
Figure: Selecting model task type (Classification or Regression) in Task Settings.


  • Click Save to confirm your task settings.
  • Finally, click Confirm on the main screen to initiate training.