In this beginner friendly course, you will learn about the Ray project and how it provides a unified compute layer for scaling deep learning applications. From data loading to model training and hyperparameter tuning to prediction and serving, we will cover how to scale each stage of your ML model lifecycle.
You will explore Ray AI Libraries that enable you to build end-to-end machine learning applications. To illustrate this, you will work with image classification, a widely recognized deep learning use case.
By the conclusion of this tutorial, you will feel confident in harnessing Ray's full potential for your own machine learning projects.