<ul><li>Machine Learning has become more accessible with tools like Amazon SageMaker, allowing users to train models from raw data easily.</li><li>The process involves uploading a dataset to an Amazon S3 bucket, setting up a SageMaker Notebook Instance, loading and exploring the data, pre-processing it, and training the model using built-in algorithms.</li><li>By following the steps outlined, users can efficiently train and deploy machine learning models using Amazon SageMaker and S3-hosted datasets.</li><li>The integration of Amazon SageMaker with S3 provides a scalable solution for training ML models, simplifying the process from data upload to model deployment.</li></ul>

Training Your First ML Model on Amazon SageMaker Using S3 Data

Discover more