Allows use of AWS ECR registries with Kubernetes no matter where your cluster is running.
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Updated
Dec 9, 2022 - Python
Allows use of AWS ECR registries with Kubernetes no matter where your cluster is running.
A Covid-19 data pipeline on AWS featuring PySpark/Glue, Docker, Great Expectations, Airflow, and Redshift, templated in CloudFormation and CDK, deployable via Github Actions.
Simple collection of tiny AWS Lambda Function that help with monitoring of ECR repositories.
The NLP Hub consists of multiple NLP services, each providing specific functionality, such as sentiment analysis, named entity recognition, grammar & spell check, and text summarization. The system is designed to handle a high volume of text data.
This repository will contain the code of an end to end ML project of House Price prediction and Housing Property recommendation as per the data scrapped from Magicbricks.com
CI/CD for discord-bot
Created BERT Named Entity Relation(NER) API
Fullstack website. Mainly built to show my skills and for everyone who needs some samples.
The Document Question and Answering RAG Application is designed to provide intelligent and accurate responses to questions based on the content of uploaded documents. By combining state-of-the-art machine learning models and cloud technologies, this application offers a seamless and scalable
Optimize your Amazon ECR repository management with the Delete Old ECR Images GitHub Action. Take charge of your container image lifecycle effortlessly: tidy up outdated images, tailor retention policies, and test with dry runs for seamless DevOps workflows.
A simple python microservice that depicts DevOps practices using Github Actions and AWS.
Secret chat built by using Flask & Python. Running in AWS. Deployed by using terraform and docker.
This is an experiment to analyze Docker images as they are pushed to an image registry
This project shows an example of a working ETL task running on AWS with containerization approach. At a high level, this app extracts raw information, transforms it by performing aggregations and stores it using the optimized file format from Apache, parquet.
This project demonstrates an event-driven architecture for parallel web scraping and processing tasks using AWS services. The scraper job, running on AWS Batch, collects data from multiple web pages simultaneously and stores it in S3. The processing job, triggered by AWS EventBridge, efficiently processes the scraped data and updates Google-Sheet.
FastAPI with DynamoDB deployed to AWS Lambda using ECR
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