BigML
Data science workflows should not require dashboard navigation. Your AI agent creates projects, configures external data connectors, and retrieves correlations from BigML's comprehensive ML platform. Predictive analytics accessible through natural language.
From project setup to data connections, your AI agent automates BigML workflows that power machine learning initiatives.
BigML
See how data teams use AI agents with BigML to set up projects, connect data sources, and manage ML resources efficiently.
A data science team starts a fraud detection project. Your AI Agent creates a project in BigML via the Create Project endpoint, setting the name, description, and category code. The team has an organized workspace ready for datasets and models without navigating setup screens.
An analyst needs to pull transaction data from a PostgreSQL database. Your AI Agent creates an external connector in BigML with connection details and source type. Data flows directly from the production database to BigML for analysis without manual export and import.
A data scientist asks which features correlate with the target variable. Your AI Agent retrieves correlation resources from BigML, lists variable relationships sorted by strength, and identifies top predictive features. Feature engineering decisions happen faster with instant statistical insights.
BigML
FAQs
The agent uses BigML's Create Project endpoint with name, description, category code, and optional tags. Projects organize datasets, models, and other resources. The agent returns the project ID for reference in subsequent operations.
The agent supports PostgreSQL, MySQL, SQL Server, and Elasticsearch through BigML's Create External Connector endpoint. Provide connection details and source type, and the agent configures the connector for direct data access.
Tars needs your BigML username and API key from your account settings. The key provides access to projects, connectors, and resources within your BigML account. Permissions follow your BigML subscription level.
No. Tars interacts with BigML APIs in real-time. Project metadata, connector configurations, and correlation results are fetched or created live. Your actual datasets and trained models remain exclusively in BigML.
The current integration focuses on project management, external connectors, and correlation analysis. For predictions, combine Tars with BigML's prediction endpoints directly or extend the agent configuration to include prediction capabilities.
The web interface requires navigation across projects, sources, and models. Tars AI Agents let you say 'Create a project for customer churn analysis' and handle setup conversationally. ML operations become accessible to non-technical stakeholders.
The agent uses BigML's Delete Project endpoint which removes the project resource. BigML handles dependencies according to your account settings. The agent can check for associated resources before deletion if configured.
WhizzML scripts automate complex ML workflows in BigML. While the agent focuses on project and connector management, it can retrieve WhizzML resources and trigger executions. Custom configurations can extend WhizzML integration.
Don't limit your AI Agent to basic conversations. Watch how to configure and add powerful tools making your agent smarter and more functional.
Privacy & Security
At Tars, we take privacy and security very seriously. We are compliant with GDPR, ISO, SOC 2, and HIPAA.
Email - sales@hellotars.com
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