Simple guide to use tf.estimator and deploy to AWS SageMaker (after training with your GPU)
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Updated
Sep 17, 2019 - Python
Simple guide to use tf.estimator and deploy to AWS SageMaker (after training with your GPU)
Run Multiple Models on the Same GPU with Amazon SageMaker Multi-Model Endpoints Powered by NVIDIA Triton Inference Server. A Java client is also provided.
Goal: Develop Machine Learning aplication in a distributed environment using AWS services with Spark.
Sample code to run Amazon SageMaker endpoint for inference with a ready model from Tensorflow Hub
This repository outlined how to implement MLOps practice on AWS Cloud using Amazon SageMaker.
fun project to train and deploy a text classification model over Women's e-commerce CLothing reviews
Jupyter notebooks to help team members utilize AWS SageMaker tools
Example of how to use word embedding with BlazingText algorithm in Amazon SageMaker on entire contents of wikipedia for a foreign language (Hebrew).
The repository contains projects and tutorials completed as a part of Udacity Machine Learning Engineer Nanodegree
Workshop CDK Template to provision infra for the Deep Visual Search workshop
A PyTorch RNN model for Sentiment Analysis deployed with AWS SageMaker
Amazon SageMaker DeepAR Spanish Workshop
An end-to-end example of a serverless machine learning pipeline for multiclass classification on AWS with SageMaker Pipelines, Data Wrangler, Athena and XGBoost.
Machine Learning on AWS using various methods/examples
A "Hello world" project on how implement your own ML Model in AWS Sagemaker.
This is a template for deploying a FastAPI endpoint on AWS SageMaker.
A small collection of custom kernels for running Sagemaker Notebooks an Training Jobs
Workshop to create a visual search engine using Amazon SageMaker and Amazon OpenSearchService
Fasttext container for Amazon Sage Maker
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