*By Mahmoud AbuAwd / AI/ML Engineer / LinkedIn Profile : https://www.linkedin.com/in/mahmoud-abuawd-247290225/*

Amazon SageMaker is a fully managed machine learning (ML) service provided by AWS (Amazon Web Services) that enables developers and data scientists to build, train, and deploy ML models quickly and at scale.

Key Features of Amazon SageMaker:

1. Integrated Jupyter notebooks for easy data exploration and preprocessing.
2. Built-in algorithms and frameworks like TensorFlow, PyTorch, and XGBoost.
3. Automatic model tuning (hyperparameter optimization).
4. Managed training and model hosting—scale up training jobs and deploy with one click.
5. Model monitoring for real-time performance metrics.
6. SageMaker Studio—a visual interface for end-to-end ML workflows.

Benefits:

• End-to-end ML lifecycle support
• Serverless inference and multi-model endpoints
• Cost-effective with pay-as-you-go pricing
• Security and compliance integration with AWS tools like IAM and VPC

Official Video (10 mins):

📺 Watch the Amazon SageMaker Overview (10 mins) by AWS

Source: AWS YouTube Channel

References:

• Amazon SageMaker – Official AWS Product Page
• Amazon SageMaker Documentation