# MLflow

#### Install mlflow using pip

```python
pip install mlflow
```

{% hint style="warning" %}
MLflow can be used in any Spark environmnet, but the automated tracking and UI of MLflow is Databricks-Specific Functionality.
{% endhint %}

Track metrics and parameters

```python
import mlflow

## Log Parameters and Metrics from your normal MLlib run
with mlflow.start_run():
  # Log a parameter (key-value pair)
  mlflow.log_param("alpha", 0.1)

  # Log a metric; metrics can be updated throughout the run
  mlflow.log_metric("AUC", 0.871827)
  mlflow.log_metric("F1", 0.726153)
  mlflow.log_metric("Precision", 0.213873)
```

MLflow GitHub: <https://github.com/mlflow/mlflow/>