sagemaker-deployment

There are 131 repositories under sagemaker-deployment topic.

  • MyMacroChef

    MyMacroChef

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  • fruits-classfication

    Fruit classification tensorflow

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  • sentiment-analysis-for-film-review

    A Notebook that allows you to determine the sentiment of a reviewer on a movie based on the rewiew that he wrote.

    Language:Jupyter Notebook2
  • Machine-Learning-On-AWS

    Machine-Learning-On-AWS

    Machine Learning on AWS using various methods/examples

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  • sentiment-analysis-sagemaker

    Deployment of sentiment analysis model using Amazon sagemaker

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  • deploying-a-sentiment-analysis-model

    A recurrent neural network deployed on SageMaker for determining the sentiment of a movie review

    Language:Jupyter Notebook2
  • SageMaker-Project

    A part of Udacity Deep Learning Nanodegree Project

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  • DL_Deploying_Sentimental_Model

    Project from Deep Learning Nanodegree - Udacity

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  • bulding-domain-expert-model-on-aws-sagemaker

    This repo hosts a proof-of-concept (poc) development for a domain expert model using the aws sagemaker meta llama 2 7B foundation model.

    Language:Jupyter Notebook1
  • Finance-Domain-Expert-LLM-Model

    Proof of concept (POC) for a domain expert model: This model will be trained on a dataset of domain-specific knowledge in finance.

    Language:Jupyter Notebook1
  • MLOps-Pipeline

    This project deploys a pre-trained GPT-2 language model on Amazon SageMaker using Hugging Face Transformers. It encompasses model download, S3 upload, SageMaker deployment, Lambda function integration, and API Gateway setup. Dedicated scripts manage these tasks, supported by a CI/CD pipeline for efficient deployment.

    Language:Jupyter Notebook1
  • sagemaker-domain-disaster-recovery

    SageMaker Domain (SageMaker Classic) Disaster Recovery

    Language:Python1
  • sagemaker-mme-gpu-triton-java-client

    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.

    Language:Java1
  • bike-rental-timeseries-forcasting-on-AWS-DeepAR

    The Amazon SageMaker DeepAR forecasting algorithm is a supervised learning algorithm for forecasting scalar (one-dimensional) time series using recurrent neural networks (RNN).When your dataset contains hundreds of related time series, DeepAR outperforms the standard ARIMA and ETS methods. You can also use the trained model to generate forecasts for new time series that are similar to the ones it has been trained on.

    Language:Jupyter Notebook1
  • bitcoin-price-oracle

    Bitcoin Price Prediction Oracle made with AWS DeepAR

    Language:Jupyter Notebook1
  • aws-ml-classification-task

    This notebook demonstrates how to leverage transfer learning to use your own image dataset to build and train an image classification model using MXNet and Amazon SageMaker.

    Language:Jupyter Notebook1
  • Sentiment-SageMaker-K8s-Operators

    An update to date SageMaker Version 2 Machine Learning endpoint building and connection with Kubernetes cluster backend with SageMaker Kubernetes Operators

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  • Project-Plagiarism-Detector

    A Notebook that allows you to check if a document is plagiarize from a known original source document.

    Language:Jupyter Notebook1
  • UDACITY-ML-Engineer-Nanodegree-Project

    As part of the ML Engineering course from Udacity, I used AWS SageMaker and S3 resources to develop a price forecaster for stocks.

    Language:Jupyter Notebook1
  • plagiarism-detector

    plagiarism-detector

    Udacity project to build a plagiarism detector that examines a text file and performs binary classification. Classification models used are Linear Learner, Random Forest Classfier and Neural Network, which are trained and deployed on AWS Sagemaker. The text file is labeled as either plagiarized or not, depending on how similar that text file is to a provided source text.

    Language:Jupyter Notebook1
  • SageMaker-Deployment

    The repository contains projects and tutorials completed as a part of Udacity Machine Learning Engineer Nanodegree

    Language:Jupyter Notebook1
  • Rainfall-Prediction

    Predict rainfall based on given parameters. Includes data preprocessing, feature selection, modelling using sagemaker.

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  • sentiment-analysis-sagemaker-deployment

    Sentiment Analysis Model Deployment Using Amazon SageMaker

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  • Deploying-a-Sentiment-Analysis-Model-on-Amazon-Sagemaker

    Deploying-a-Sentiment-Analysis-Model-on-Amazon-Sagemaker using Pytorch

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  • Machine-Learning-Engineer-Udacity

    Udacity Nanodegree Exercises and Projects

    Language:Jupyter Notebook1
  • plagiarism_detector_sagemaker

    Plagiarism Detector using AWS Sagemaker

    Language:Jupyter Notebook1
  • bert-deployment-aws

    Code for the FullStack AI Live Coding Series- Part 3 (CellStrat AI Lab)

    Language:Jupyter Notebook1
  • Natural-Language-Processing

    The repository for NLP projects like Sentiment Analysis, Part of Speech, Topic Modeling, Machine Translation, Chatbox, DNN speech Recognizer etc.

    Language:Python1
  • plagiarism-detection

    Contains solution for plagiarism detection project (2nd project of ml nanodegree udacity) .Uses two features contaiment and longest common subsequence to identify plagiarism.

    Language:Jupyter Notebook1
  • aws-deployment

    This is the solution for the project -1 (AWS Deployment) that I developed for machine learning Nanodegree. It contains code for deploying a sentiment analysis model from imdb dataset on AWS Sagemaker.

    Language:Jupyter Notebook1
  • sentiment-analysis-sagemaker-deployment

    In this project we will construct a recurrent neural network for the purpose of determining the sentiment of a movie review using the IMDB data set. we will create this model using Amazon's SageMaker service. In addition, we will deploy our model and construct a simple web app which will interact with the deployed model.

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  • Sentiment-Analysis

    Sentiment Analysis on movie reviews

    Language:Jupyter Notebook1
  • HuggingFaceModelDeployment_AWS_Sagemaker

    This project is about deploying HuggingFace model(distilbert-base-uncased-distilled-squad) on AWS sagemaker for the task of question Answering. The model is configured ,IAM role is created for permissions to create endpoint and the model is deployed to Sagemaker Inference.

    Language:Jupyter Notebook
  • Notebook

    Credit Card Fraud Detection Model with an accuracy of 91.24%.Uses AWS for training and tuning.

    Language:Jupyter Notebook