How Determined Works

With Determined you can:

• Use state-of-the-art distributed training to train models faster without changing model code.

• Automatically find high-quality models using advanced hyperparameter tuning.

• Get more from your GPUs and reduce cloud GPU costs with preemptible instances and smart scheduling.

• Leverage experiment tracking out-of-the-box to track and reproduce your work, tracking code versions, metrics, checkpoints, and hyperparameters.

• Continue using popular deep learning libraries, such as TensorFlow, Keras, and PyTorch by simply integrating the Determined API with your existing model code.

Determined integrates these features into an easy-to-use, high-performance deep learning environment so you can spend your time building models instead of managing infrastructure.

Learn more:

• Intro to Determined: Conceptual information about Determined including its features and benefits.

• System Architecture: Learn about the main components of the Determined system architecture.

• Distributed Training: A conceptual overview of distributed training with Determined.