Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.

Probabilistic time series modeling in Python

A library for training and deploying machine learning models on Amazon SageMaker

AWS Deep Learning Containers (DLCs) are a set of Docker images for training and serving models in TensorFlow, TensorFlow 2, PyTorch, and MXNet.

Create and share production-quality backend apps and services anywhere. Unobtrusive, debuggable, PyTorch-like APIs for your world of infra.

A modular and comprehensive solution to deploy a Multi-LLM and Multi-RAG powered chatbot (Amazon Bedrock, Anthropic, HuggingFace, OpenAI, AI21, Cohere) using AWS CDK on AWS

Example notebooks for working with SageMaker Studio Lab. Sign up for an account at the link below!

Training deep learning models on AWS and GCP instances

Train machine learning models within a 🐳 Docker container using 🧠 Amazon SageMaker.

MLOps for AWS SageMaker

Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...

Large scale and asynchronous Hyperparameter and Architecture Optimization at your fingertips.

Serve machine learning models within a 🐳 Docker container using 🧠 Amazon SageMaker.

A Spark library for Amazon SageMaker.

Toolkit for running TensorFlow training scripts on SageMaker. Dockerfiles used for building SageMaker TensorFlow Containers are at https://github.com/aws/deep-learning-containers.

Library for automatic retraining and continual learning

Setup end to end demo architecture for predicting fraud events with Machine Learning using Amazon SageMaker

Amazon SageMaker Local Mode Examples

An end-to-end blueprint architecture for real-time fraud detection(leveraging graph database Amazon Neptune) using Amazon SageMaker and Deep Graph Library (DGL) to construct a heterogeneous graph from tabular data and train a Graph Neural Network(GNN) model to detect fraudulent transactions in the IEEE-CIS dataset.

Toolkit for running PyTorch training scripts on SageMaker. Dockerfiles used for building SageMaker Pytorch Containers are at https://github.com/aws/deep-learning-containers.