In this chapter, we studied how Amazon SageMaker offers various ready-to-use machine learning models to generate predictions, as well as algorithm images that can be used to train your models. Amazon SageMaker generates a layer of abstraction between you and the messy details of setting up your own clusters to train and create your own machine learning model. Amazon SageMaker dashboards also offer a place to store your trained models and monitor your batch processing jobs for predictions.
You can also train your own machine learning models using your own datasets in SageMaker. We presented an example of training a machine learning model that is capable of performing object detection in images. We demonstrated how this model can then be deployed on SageMaker and used for running batch prediction jobs. You will be able to use this as a template to work on other algorithms...
