(Unofficial) curated list of awesome workshops found around in the internet. As we all have been there, finding that workshop that you have just attended shouldn't be hard. The idea is to provide an easy central repository, in a collaborative way.

A Spark library for Amazon SageMaker.

Amazon SageMaker Local Mode Examples

A helper library to connect into Amazon SageMaker with AWS Systems Manager and SSH (Secure Shell)

Safe blue/green deployment of Amazon SageMaker endpoints using AWS CodePipeline, CodeBuild and CodeDeploy.

Open innovation with 60 minute cloud experiments on AWS

MLOps workshop with Amazon SageMaker

Hands-on demonstrations for data scientists exploring Amazon SageMaker

Deploy Generative AI models from Amazon SageMaker JumpStart using AWS CDK

Docker images that replicate the Amazon SageMaker Notebook instance.

Demonstration of Natural Language Query (NLQ) of an Amazon RDS for PostgreSQL database, using SageMaker JumpStart, Amazon Bedrock, LangChain, Streamlit, and Chroma.

Amazon SageMaker Managed Spot Training Examples

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.

Running your TensorFlow models in Amazon SageMaker

Snowflake Guide: Building a Recommendation Engine Using Snowflake & Amazon SageMaker

End to end Machine Learning with Amazon SageMaker

Amazon SageMaker で MLOps (前処理・学習・評価・推論、および、実験・モデル・ワークフローの管理) を実現するミニマムなコードサンプル

This repo contains various use-cases of deep-learning implemented in Pytorch. It also contains summarized notes of each chapter from the book, 'Deep Learning' written by Ian Goodfellow.

'Talk to your slide deck' (Multimodal RAG) using foundation models (FMs) hosted on Amazon Bedrock and Amazon SageMaker