brunopistone

awesome-sagemaker

A curated list of references for Amazon SageMaker

amazon-bedrock-samples

This repository contains examples for customers to get started using the Amazon Bedrock Service. This contains examples for all availble foundational models

genai-qa-rag

llm-evaluation-ragas-api-gateway

nginx-vue-docker

My website realized with vuejs framework

sagemaker-notebook-jobs-interactive-session

sagemaker-processing-spark

sagemaker-training-estimator

sm-end-to-end-mlops

This is a sample code repository for demonstrating how to organize your code for build and train your model, by starting from an implementation through notebooks for arriving to a code structure architecture for implementing ML pipeline using Amazon SageMaker Pipeline, and how to setup a repository for deploying ML models using CI/CD. This repo is based on a NLP project for sentiment analysis

vue-separated-html-without-webpack

Vue webapplication with separated vue javascript components from their html

brunopistone/nginx-vue-docker

My website realized with vuejs framework

brunopistone/genai-qa-rag

brunopistone/sagemaker-processing-spark

brunopistone/vue-separated-html-without-webpack

Vue webapplication with separated vue javascript components from their html

brunopistone/llm-evaluation-ragas-api-gateway

brunopistone/sagemaker-notebook-jobs-interactive-session

brunopistone/sagemaker-training-estimator

brunopistone/sm-end-to-end-mlops

This is a sample code repository for demonstrating how to organize your code for build and train your model, by starting from an implementation through notebooks for arriving to a code structure architecture for implementing ML pipeline using Amazon SageMaker Pipeline, and how to setup a repository for deploying ML models using CI/CD. This repo is based on a NLP project for sentiment analysis

brunopistone/amazon-bedrock-samples

This repository contains examples for customers to get started using the Amazon Bedrock Service. This contains examples for all availble foundational models

brunopistone/amazon-sagemaker-examples

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

brunopistone/amazon-sagemaker-spark-ui

brunopistone/awesome-sagemaker

A curated list of references for Amazon SageMaker

brunopistone/aws-neuron-samples

brunopistone/flan-t5-multi-language

brunopistone/gradle-springboot-jersey

Sample of a webapp using gradle, Springboot, Jersey and AngularJS

brunopistone/java-springboot-angularjs-nginx-docker

brunopistone/ml-edge-getting-started

brunopistone/multi-model-train-template

The purpose of this template is to deploy a Sagemaker Training Pipeline for parallel training of multiple models, and a scheduled batch inference using SageMaker Batch Transform and SageMaker Pipelines, given two `ModelGroupPackageName` from the Amazon SageMaker Model Registry.

brunopistone/sagemaker-custom-project-templates

brunopistone/sagemaker-framework-processor

brunopistone/sagemaker-ssh-helper

A helper library to connect into Amazon SageMaker with AWS Systems Manager and SSH

brunopistone/search-app

brunopistone/sm-iot-end-to-end

This is a sample code repository for demonstrating how to organize your code for build and train your model, by starting from an implementation through notebooks for arriving to a code structure architecture for implementing ML pipeline using Amazon SageMaker Pipeline, and how to setup a repository for deploying ML models using CI/CD.