Use it when
- You want to parallelize your machine learning computation across several machines.
- You want a general-purpose distributed computing library that supports heterogeneous workloads and is not restricted to structured data.
- You want to seamlessly scale your code from your local machine to a cluster.
- You want high-level libraries that support model training, hyperparameter tuning, building pipelines, and serving models.
Example stacks
Airflow + MLflow stack
Installation
pip install ray