Generating Cat images using StyleGAN

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

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.

AWS Machine Learning Engineer Scholarship Program

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

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.

Udacity DLND Project

Training and deploying sentiment analysis models with deep learning using Amazon SageMaker. A BERT model was trained using distributed training with the help of Hugging Face.

Automated KYC Verification for Businesses

A deployed RNN performing sentiment analysis on movie reviews complete with publicly accessible API and a simple web page which interacts with the deployed endpoint.

Build and deploy a ML model using AWS SageMaker

Sentiment Analysis Model Deployment Using Amazon SageMaker

This repository is create SageMaker model and invoke endpoint.

A web app hosted on aws, which finds the sentiment of movie review i.e. if it is positive or not.

Operationalizing an AWS ML Project

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

Deploying a Sentiment Analysis Model

This repo contains the first project of Udacity Machine Learning Engineer NanoDegree program.

Building a scalable and safe image classification model on Amazon Sagemaker implemented with AWS Lambda Functions for supporting services and AWS Step Functions to merge them into an an event-driven application