The Data Science Platform (TuringTurbo) is a machine learning and deep learning model training management platform.
Designed for customers who need to conduct machine learning, deep learning, predictive analysis, and intelligent decision-making, it provides a project-based, team-collaborative AI modeling closed loop. The platform covers the entire process from data ingestion, data processing, model creation, model training, model evaluation, model inference, model deployment to model services, and is equipped with data annotation, resource monitoring, permission management, and an AI model marketplace, helping customers advance algorithmic capabilities from experimental verification to operational and reusable production services.
Multi-Source Training Data Ingestion: Supports data source access from various types of databases and local files, providing a unified data entry point for modeling.
Data Exploration and Feature Engineering: Provides capabilities for data cleaning, filtering, processing, feature extraction, normalization, standardization, correlation analysis, and feature selection.
Multi-Mode Model Development: Supports Flow visual modeling, Notebook IDE modeling, and automated modeling, balancing low-barrier configuration with in-depth development.
Model Training and Evaluation Closed Loop: Supports training task monitoring, parameter tuning, evaluation metrics, and model reports, helping teams assess model quality and continuously optimize.
Model Inference and Deployment Services: Supports model inference, result export, model engine encapsulation, and rapid deployment to production, providing standard service interfaces externally.
Production Monitoring and Model Marketplace: Provides security validation, permission verification, elastic scaling, resource monitoring, and model asset accumulation, supporting long-term operational reuse of models.