Creating notebooks in Amazon SageMaker
If you're working with machine learning, then you need to perform actions such as storing data, processing data, preparing data for model training, model training, and deploying the model for inference. They are not easy, and each of these stages requires a machine to perform the task. With Amazon SageMaker, life becomes much easier when carrying out these steps.
What is Amazon SageMaker?
SageMaker provides training instances to train a model using the data and provides endpoint instances to infer by using the model. It also provides notebook instances, running Jupyter Notebooks, to clean and understand the data. If you're happy with your cleaning process, then you should store them in S3 as part of the staging for training. You can launch training instances to consume this training data and produce a machine learning model. The machine learning model can be stored in S3, and endpoint instances can consume the model to produce...
