Generating Cat images using StyleGAN

Deep Learning Udacity Nanodegree - SageMaker Deployment of a Sentiment Analysis model

Automated KYC Verification for Businesses

Build and deploy a ML model using AWS SageMaker

An end-to-end MLOps pipeline that reads data from PrestoDB to train an ML model and deploy on SageMaker for batch and realtime inference.

Sentiment Analysis Model Deployment Using Amazon 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.

Fraud Detection of a 6 million row dataset using AWS and Spark

Deploying a Pytorch model in Amazon SageMaker and connecting a web app to it

Machine learning models are used to determine whether a house is a good potential "flip" or not, using standard 70% rule.

Operationalizing an AWS ML Project

Udacity Machine Learning Nanodegree Project: Deploy a Sentiment Analysis Model

AWS Machine Learning Engineer Scholarship Program

Udacity DLND Project

Movie Reviews Sentiment Analysis.

Deploying a Pytorch model in Amazon Sagemaker and access it through open endpoint Amazon Lambda function

Sentiment Analysis of the IMDB data set using SageMaker

RF Signals ML demo with SpectrumSens system for hackathon AWS Disaster Response.

Project for Deep Learning Nanodegree, unit 6 (Deploying a Model).

Deploying a Sentiment Analysis Model