Artificial Intelligence
Author: Arunprasath Shankar
Make batch predictions with Amazon SageMaker Autopilot
March 2025: This post was reviewed and updated for accuracy. Amazon SageMaker Autopilot is an automated machine learning (AutoML) solution that performs all the tasks you need to complete an end-to-end machine learning (ML) workflow. It explores and prepares your data, applies different algorithms to generate a model, and transparently provides model insights and explainability […]
Save costs by automatically shutting down idle resources within Amazon SageMaker Studio
July 2023: This post was reviewed for accuracy. The Github repository is maintained up to date. Amazon SageMaker Studio provides a unified, web-based visual interface where you can perform all machine learning (ML) development steps, making data science teams up to 10 times more productive. Studio gives you complete access, control, and visibility into each […]
Host multiple TensorFlow computer vision models using Amazon SageMaker multi-model endpoints
Amazon SageMaker helps data scientists and developers prepare, build, train, and deploy high-quality machine learning (ML) models quickly by bringing together a broad set of capabilities purpose-built for ML. SageMaker accelerates innovation within your organization by providing purpose-built tools for every step of ML development, including labeling, data preparation, feature engineering, statistical bias detection, AutoML, […]
Enable feature reuse across accounts and teams using Amazon SageMaker Feature Store
October 2023: This post was reviewed and updated for accuracy. Amazon SageMaker Feature Store is a new capability of Amazon SageMaker that helps data scientists and machine learning (ML) engineers securely store, discover, and share curated data used in training and prediction workflows. As organizations build data-driven applications using ML, they’re constantly assembling and moving […]