training-machine-learning-models

Automates ML model training, evaluation, and persistence with data analysis and cross-validation.

• Trains ML models on datasets with automatic data analysis.
• Identifies target variables and selects appropriate model types.
• Evaluates model performance using metrics like accuracy and MSE.
• Saves trained model artifacts for future use.

• Analyzes dataset to identify target variable and model type.
• Uses cross-validation for robust model training.
• Generates performance metrics (e.g., accuracy, MSE, R-squared).
• Automates full ML pipeline: analysis, training, evaluation.
• Persists trained model as a reusable artifact.
• Integrates with data and model deployment tools.
• Supports both classification and regression tasks.
• Requires clean, properly formatted data input.

1. 1.Provide a dataset with a clear target variable.
2. 2.Specify the type of model needed (classification or regression).
3. 3.Let the skill analyze, train, and evaluate the model automatically.