Data Science Lab
  • What is Data Science Lab?
  • Accessing the Data Science Lab Module
  • Data Science Lab Quick Start Flow
  • Project
    • Environments
    • Creating a Project
    • Project List
      • View
      • Keep Multiple Versions of a Project
      • Sharing a Project
      • Editing a Project
      • Activating a Project
      • Deactivating a Project
      • Deleting a Project
    • Tabs for a Data Science Lab Project
      • Tabs for TensorFlow and PyTorch Environment
        • Notebook
          • Ways to Access Notebook
            • Create
            • Import
              • Importing a Notebook
              • Pull from Git
          • Notebook Page
            • Preview Notebook
            • Notebook Cells
              • Using a Code Cell
              • Using a Markdown Cell
              • Using an Assist Cell
            • Renaming a Notebook
            • Resource Utilization Graph
            • Notebook Taskbar
            • Notebook Operations
              • Datasets
                • Copy Path (for Sandbox files)
              • Secrets
              • Algorithms
              • Transforms
              • Utility
              • Models
                • Model Explainer
                • Registering & Unregistering a Model
                • Model Filter
              • Artifacts
              • Files
              • Variable Explorer
              • Writers
              • Find and Replace
            • Notebook Actions
          • Notebook List
            • Notebook List Actions
              • Export
                • Export to Pipeline
                • Export to GIT
              • Register as Job
              • Notebook Version Control
              • Sharing a Notebook
              • Deleting a Notebook
        • Dataset
          • Adding Data Sets
            • Data Sets
            • Data Sandbox
          • Dataset List Page
            • Preview
            • Data Profile
            • Create Experiment
            • Data Preparation
            • Delete
        • Utility
          • Pull from Git (Utility)
        • Model
          • Model Explainer
          • Import Model
          • Export to GIT
          • Register a Model
          • Unregister A Model
          • Register a Model as an API Service
            • Register a Model as an API
            • Register an API Client
            • Pass Model Values in Postman
          • AutoML Models
        • Auto ML
          • Creating AutoML Experiments
            • Creating an Experiment
          • AutoML List Page
            • View Report
              • Details
              • Models
                • View Explanation
                  • Model Summary
                  • Model Interpretation
                    • Classification Model Explainer
                    • Regression Model Explainer
                    • Forecasting Model Explainer
                  • Dataset Explainer
            • Delete
      • Tabs for PySpark Environment
        • Notebook
          • Ways to Access Notebook
            • Create
            • Import
              • Importing a Notebook
          • Notebook Page
            • Preview Notebook
            • Notebook Cells
              • Using a Code Cell
              • Using a Markdown Cell
              • Using an Assist Cell
            • Renaming a Notebook
            • Resource Utilization Graph
            • Notebook Taskbar
            • Notebook Operations
              • Datasets
                • Copy Path (for Sandbox files)
              • Secrets
              • Utility
              • Files
              • Variable Explorer
              • Writers
              • Find and Replace
            • Notebook Actions
          • Notebook List
            • Notebook List Actions
              • Export
                • Export to Pipeline
                • Export to GIT (on hold)
              • Register as Job
              • Notebook Version Control
              • Sharing a Notebook
              • Deleting a Notebook
        • Dataset
          • Adding Data Sets
            • Data Sets
            • Data Sandbox
          • Dataset List Page
            • Preview
            • Data Profile
            • Data Preparation
            • Delete
        • Utility
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On this page
  1. Project
  2. Tabs for a Data Science Lab Project
  3. Tabs for TensorFlow and PyTorch Environment
  4. Auto ML

Creating AutoML Experiments

A Data Scientist can create various Experiments based on specified algorithms.

PreviousAuto MLNextCreating an Experiment

Last updated 1 year ago

There can be different types of Experiments based on the algorithm type specified. In the DS Lab module we currently support Classification, Regression, and Forecasting.

  • A Classification experiment can be created for discrete data when the user wants to predict one of the several categories.

  • A Regression experiment can be created for continuous numeric values.

  • A Forecasting experiment can be created for predicting future values based on the historical data.

Please Note:

  • AutoML experiments are running as Jobs and a new Job will get allocated for each experiment created in the AutoML tab.

  • Jobs will spin up once Experiment is created and after models are trained and ready, it will get killed automatically.

  • Refer the page to get an overview of the Data Science Lab module in nutshell.

Data Science Lab Quick Start Flow