Hands-on end-to-end workshop to explore Amazon SageMaker.

Implementation of Protein Classification based on subcellular localization using ProtBert(Rostlab/prot_bert_bfd_localization) model from Hugging Face library, based on BERT model trained on large corpus of protein sequences.

Implementation of Image Classification using Visual Transformers in Amazon SageMaker based on the ideas from research paper - Visual Transformers: Token-based Image Representation and Processing for Computer Vision.

Workshop to launch Amazon SageMaker Studio domain using AWS Service Catalog and AWS SSO in the AWS Control Tower environment, using AWS CloudFormation templates and lambda functions.

Explore the capabilities of transformer models available on Hugging Face to accomplish common NLP tasks on Amazon SageMaker using real-time and batch inference.

The Build with AWS app simplifies selecting from over 200 AWS services by analyzing project details and recommending tailored solutions. It provides step-by-step integration guidance and features AI-driven recommendations, real-time chat support, and curated AWS resources.

Build end-to-end Data Science (NLP) project for Amazon's Product Review Sentiment Classification using AWS tools.