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.

Automated KYC Verification for Businesses

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.

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.

Udacity DLND Project

DataVerse is an innovative platform that empowers users with advanced data analysis tools, enabling exploration of various data mining techniques and machine learning models to extract meaningful insights from their data.

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.

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

This repository is create SageMaker model and invoke endpoint.

Sentiment Analysis Model Deployment Using Amazon SageMaker

Operationalizing an AWS ML Project

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

This project leverages AutoGluon in AWS SageMaker Studio to predict bike sharing demand, automating model training and tuning for accurate forecasting.