Machine-Learning-Platform-as-a-Service (ML PaaS) is one of the fastest growing services in the public cloud. It delivers efficient lifecycle management of machine learning models.
At a high level, there are three phases involved in training and deploying a machine learning model. These phases remain the same from classic ML models to advanced models built using sophisticated neural network architecture.
Provision and Configure Environment
Before the actual training takes place, developers and data scientists need a fully configured environment with the right hardware and software configuration.
Read more at The New Stack
