sagemaker-deployment
There are 136 repositories under sagemaker-deployment topic.
udacity/ML_SageMaker_Studies
Case studies, examples, and exercises for learning to deploy ML models using AWS SageMaker.
anubhavshrimal/Machine-Learning
The projects I do in Machine Learning with PyTorch, keras, Tensorflow, scikit learn and Python.
aws-samples/amazon-sagemaker-mlops-workshop
MLOps workshop with Amazon SageMaker
aws-samples/amazon-sagemaker-endpoint-deployment-of-fastai-model-with-torchserve
Deploy FastAI Trained PyTorch Model in TorchServe and Host in Amazon SageMaker Inference Endpoint
aws-samples/whisper-audio-inference-for-amazon-sagemaker
This is a short example showing how to utilize Amazon SageMaker's real time endpoints with OpenAI's open source Whisper model for audio transcription.
awslabs/sagemaker-defect-detection
Detect Defects in Products from their Images using Amazon SageMaker
giuseppeporcelli/end-to-end-ml-sm
End to end Machine Learning with Amazon SageMaker
aws-samples/deploy-stable-diffusion-model-on-amazon-sagemaker-endpoint
Deploy Stable Diffusion Model on Amazon SageMaker Endpont
aws-samples/aws-mlops-pipelines-terraform
MLOps on AWS using Amazon SageMaker Pipelines
aws-samples/amazon-sagemaker-predictive-maintenance-deployed-at-edge
This workshop will familiarize you with some of the key steps towards building an end-to-end predictive maintenance system leveraging Amazon SageMaker, Amazon Polly and the AWS IoT suite.
aorabdel/Udacity-Deep-Learning-Nanodegree
My Projects Submission to Udacity's Deep Learning Nanodegree Program
bentoml/aws-sagemaker-deploy
Fast model deployment on AWS Sagemaker
aws-samples/amazon-sagemaker-predict-accessibility
Build end-to-end Machine Learning pipeline to predict accessibility of playgrounds in NYC
Jithsaavvy/Sentiment-analysis-from-MLOps-paradigm
This project promulgates an automated end-to-end ML pipeline that trains a biLSTM network for sentiment analysis, experiment tracking, benchmarking by model testing and evaluation, model transitioning to production followed by deployment into cloud instance via CI/CD
aws-samples/sagemaker-multi-model-endpoint-tensorflow-computer-vision
In this repo, we show how to host two computer vision models trained using the TensorFlow framework under one SageMaker multi-model endpoint.
aws-samples/amazon-sagemaker-endpoint-deployment-of-siamese-network-with-torchserve
Twin Neural Network Training with PyTorch and fast.ai and its Deployment with TorchServe on Amazon SageMaker
victor369basu/SagemakerHuggingfaceDashboard
This is a solution that demonstrates how to train and deploy a pre-trained Huggingface model on AWS SageMaker and publish an AWS QuickSight Dashboard that visualizes the model performance over the validation dataset and Exploratory Data Analysis for the pre-processed training dataset.
aws-samples/reinvent2021-aim408-high-performance-cost-effective-model-deployment-amazon-sagemaker
This repo contains demo code for reInvent2021 session AIM408 Achieve high performance and cost-effective model deployment
hjlopes/sagemaker-sentiment-analysis
Deep Learning Udacity Nanodegree - SageMaker Deployment of a Sentiment Analysis model
aws-samples/amazon-sagemaker-pipeline-deploy-manage-100x-models-python-cdk
This GitHub repository showcases the implementation of a comprehensive end-to-end MLOps pipeline using Amazon SageMaker pipelines to deploy and manage 100x machine learning models. The pipeline covers data pre-processing, model training/re-training, hyperparameter tuning, data quality check,model quality check, model registry, and model deployment.
eswar3/sentiment-analysis-sagemaker-deployment
Project from Deep Learning Nanodegree - Udacity
enginBozkurt/deep-learning-nanodegree
Udacity Deep Learning Nanodegree Projects
haythemtellili/NLP-Multilabel-classification
Train Multilabel NLP Classification using Pytroch and huggingface with deployment using Amazon SageMaker
prateeksawhney97/Plagiarism-Detector-Using-SageMaker
Second project of the Udacity Machine Learning Engineer Nanodegree program where a Plagiarism Detector is created using custom similarity features amongst source and answer file such as containment and longest common subsequence. Further, trained and deployed the model on Amazon Sagemaker.
developers-cosmos/Explore-AWS-Quicksight
This Repository Contains Detailed Explanation of AWS QuickSight's Latest feature( Augmenting QuickSight WIth SageMaker) . It Also Contains Deploying your own models in SageMaker AWS.
salehsargolzaee/Deploy-PyTorch-Model-using-SageMaker
Deploying a PyTorch model using AWS SageMaker
brian-kipkoech-tanui/sagemaker-ML-workflow
Image Classifiers are used in the field of computer vision to identify the content of an image and it is used across a broad variety of industries, from advanced technologies like autonomous vehicles and augmented reality, to eCommerce platforms, and even in diagnostic medicine.
ChaitanyaC22/Udacity-AWS-MLE-ND-Project2-Build-a-ML-Workflow-For-Scones-Unlimited-On-Amazon-SageMaker
The primary objective of this project was to build and deploy an image classification model for Scones Unlimited, a scone-delivery-focused logistic company, using AWS SageMaker.
flrngel/simple-estimator-and-sagemaker
Simple guide to use tf.estimator and deploy to AWS SageMaker (after training with your GPU)
Asad-Ismail/fruits-classfication
Fruit classification tensorflow
aws-samples/amazon-sagemaker-workshop-for-huggingface
Workshop for running HuggingFace Models on Amazon SageMaker.
aws-samples/optimize-foundation-models-deployment-on-amazon-sagemaker
In this workshop, we demonstrate how to choose the right container and right instance types, optimize container parameters, and set up the right autoscaling policies and how to use APIs to get recommendations with Amazon SageMaker
GOVINDDIXIT/Movie-Reviews-Sentiment-Analysis
Part of Udacity Nanodegree
jcpsantiago/sagemaker-multimodel-R
AWS Sagemaker Multi-Model Server for R
Physicist91/sentiment-analysis
Deploying sentiment analysis model with Sagemaker trained on the IMDB dataset using LSTM in PyTorch
just4give/llm-sagemaker-fargate-api
This repository contains two major projects that work together to deploy and serve Large Language Models (LLMs) on AWS SageMaker.