feat: enhance training and experiment tracking functionality

- Updated `Activities` class to improve garbage collection handling.
- Enhanced error messaging in `ExperimentTracking` for better clarity on update failures.
- Refactored `Training` class to streamline exception handling and improve type hints.
- Introduced new methods in `TrainModelParams` for better handling of experiment run IDs and model metadata.
- Added functionality to extract model equations in `DataManagerRepository` for linear regression models.

tests/sientia/test_models.py

@@ -867,6 +867,13 @@ def test_linear_regression_model_get_regressor():
 # ============================================================================
 
 
+def test_data_preprocessor_parse_datetime_with_frontend_format():
+    """When date_format is set, _parse_datetime uses strftime mapping (covers format branch)."""
+    preprocessor = DataPreprocessor(date_format='dd/MM/yyyy HH:mm:ss')
+    ts = preprocessor._parse_datetime('15/01/2024 10:30:00')
+    assert ts is not None
+
+
 @patch('model_manager.sientia.models.treat_nan')
 def test_data_preprocessor_treat_discontinuities_linear_interpolation(mock_treat_nan):
     """Test treat_discontinuities with 'linear interpolation' treatment."""