datarobot-model-training

# DataRobot Model Training Skill This skill provides guidance for the complete model training workflow in DataRobot, from project creation through model selection and validation. ## Quick Start **Most common use case**: Create a project and train models 1. **Upload dataset**: `upload_dataset(file_path, dataset_name)` to upload training data 2. **Create project**: `create_project(dataset_id, project_name)` to create new project 3. **Start training**: `start_automl(project_id, mode)` to begin AutoML training **Example**: "Create a new project with sales_data.csv, set 'revenue' as target, and start Quick AutoML training" ## When to use this skill Use this skill when you need to: - Create new DataRobot projects - Upload training datasets - Configure AutoML experiments - Monitor training progress - Select and compare models - Understand feature engineering results - Export trained models ## Key capabilities ### 1. Project Management - Create new projects with appropriate settings - Upload datasets (CSV, Parquet, database connections) - Configure project settings (target, partitioning, time series) - Manage multiple projects and experiments ### 2. AutoML Configuration - Set training modes (Quick, Manual, Comprehensive) - Configure feature engineering options - Set time limits and resource constraints - Choose algorithms and model types ### 3. Training Execution - Start AutoML training runs - Monitor training progress - Handle training errors and warnings - Pause/resum...