MLCOST-12: Select an optimal ML framework

Use Amazon SageMaker AI Experiments - Amazon SageMaker AI Experiments lets you organize, track, compare, and evaluate your machine learning experiments. Using this service, you can experiment with various ML frameworks and see which one gives you the most cost-effective performance. AWS Deep Learning AMIs and AWS Deep Learning Containers enable you to use several open-source ML frameworks for training on your infrastructure. AWS Deep Learning AMIss have popular deep learning frameworks and interfaces preinstalled including TensorFlow, PyTorch, Apache MXNet, Chainer, Gluon, Horovod, and Keras. The AMI or container can be launched on powerful infrastructure that has been optimized for ML performance. SageMaker AI also allows you to bring your own container where you can use any framework you choose.

Use Machine Learning Frameworks, Python, and R with Amazon SageMaker AI

Right-sizing resources and avoiding unnecessary costs in Amazon SageMaker AI

Amazon SageMaker AI Experiments – Organize, Track and Compare your Machine Learning Trainings