Amazon SageMaker

Amazon SageMaker is a machine learning solution that enables data scientists and developers to create, train and deploy machine learning models. It supports batch and online learning, and comes with pre-built algorithms for common use cases.

It has an intuitive user interface, powerful algorithms and an enterprise-grade infrastructure that allows you to build your machine learning solution without having to be an expert in cloud infrastructure or deep learning.

SageMaker also has a library of machine learning tools that you can use without having to install any other software. Cloud service features include:

  • Automated machine learning (AutoML) capabilities that allow developers to create machine learning models with little or no prior experience in the field, and use pre-built algorithms such as deep learning algorithms, reinforcement learning algorithms, generative adversarial networks (GANs), and natural language processing (NLP) algorithms.


  • Model tuning: SageMaker's hyperparameter tuning capabilities are used to find the best set of values for a model's parameters. This feature is particularly useful if the model requires multiple hyperparameters.


  • Model optimisation: SageMaker can optimise the model's parameters to reduce its cost function, which helps to achieve better performance using fewer resources.


  • Deployment: Once the model is ready to run, it can be deployed on a variety of platforms, including AWS Lambda, Amazon ECR, or Amazon EC2 instances.


  • A web-based user interface makes it easy to manage and monitor machine learning models, and perform tasks such as hyperparameter tuning and model training.