mrvaldemar,Mr. Valdemar,github

amazon-personalize-samples

Notebooks and examples on how to onboard and use various features of Amazon Personalize

amazon-sagemaker-examples

Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker

amazon-transcribe-news-media-analysis

Transcribe news audio in realtime.

automating-aws-migration-with-cloudendure-scripts

Automating AWS Migration with CloudEndure Scripts to accelerate the migration and reduce migration errors

aws-ai-ml-workshop-kr

A collection of localized (Korean) AWS AI/ML workshop materials for hands-on labs.

This software compares the output and running time of the EMR cluster. The architecture has been designed that users can throw(like shooting) a request, and receive a result(like score) by email, as if they were playing a basketball game.

aws-greengrass-lambda-functions

Example local Lambda functions that can be used with AWS Greengrass and the AWS Greengrass Provisioner.

aws-greengrass-samples

Samples for AWS Greengrass

aws-ml-detection-workshop

This workshop shows how you can use an IP-based machine learning algorithm with Amazon SageMaker to augment and enrich findings from AWS Security services such as Amazon GuardDuty. You'll learn how to load the notebook in SageMaker, train the model, and score findings to determine abnormality of the activity.

aws-ml-guide

AWS Certified Machine Learning-Specialty (ML-S) Guide

aws-sagemaker-build

Creates a CloudFormation template that uses AWS StepFunctions to automate the building and training of Sagemaker custom models based on S3 and GitHub events

aws-sam-cli

CLI tool to build, test, debug, and deploy Serverless applications using AWS SAM

aws-shell

An integrated shell for working with the AWS CLI.

ml-gameday-tutorial

This repository contains code and guides for getting your team quickly started with the ML gameday event.

sagemaker-containers

This support code is used for making machine learning frameworks (e.g. MXNet, TensorFlow) run on Amazon SageMaker.

sagemaker-deployment

Code and associated files for the deploying ML models within AWS SageMaker

sagemaker-examples

SageMaker listado de ejercicios

sagemaker-pipeline

Sagemaker pipeline for AWS Summit New York

sagemaker-python-sdk

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

serverless-application-model

AWS Serverless Application Model (SAM) is an open-source framework for building serverless applications

serverless-sagemaker-orchestration

This example shows how to build a serverless pipeline to orchestrate the continuous training and deployment of a linear regression model for predicting housing prices using Amazon SageMaker, AWS Step Functions, AWS Lambda, and Amazon CloudWatch Events.

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