Basem Khalaf 's Projects
Apache Airflow tutorial
Example š Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using š§ Amazon SageMaker.
A CloudFormation template that creates a multi-region Disaster Recovery environment for Amazon WorkSpaces.
Amundsen is a metadata driven application for improving the productivity of data analysts, data scientists and engineers when interacting with data.
Checklist of the most important security countermeasures when designing, testing, and releasing your API
Arduino As Esp8266 Uploader
Creating AuroraDB Postgresql, and connect it with pgAdmin, then populate the data/tables and finally querying the data by sql.
A serverless architecture for orchestrating ETL jobs in arbitrarily-complex workflows using AWS Step Functions and AWS Lambda.
A Data Platform built for AWS, powered by Kubernetes.
AWS SaaS Boost is a ready-to-use toolset that removes the complexity of successfully running SaaS workloads in the AWS cloud.
This tutorial is to test the notebooks of sagemaker service for building machine learning models on the cloud.
Virtual Container for all my architectures, DevOps, Cloud and Data Engineering solutions.
My personal profile and Github projects store.
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A tool for cleaning up your cloud accounts by nuking (deleting) all resources within it
This is test machine learning CI/CD pipeline.
All My Colab_Notbooks
University of Washington
Code for Data Engineer Zoomcamp course
:bar_chart: Path to a free self-taught education in Data Science!
Collection of useful data science topics along with code and articles
The repo contains all my works done during the data engineering zoomcamp with 4 talented and experienced data engineers.
Template for Data Engineering and Data Pipeline projects
Learn Pytorch, Sagemaker & Computer Vision in General
Roadmap to becoming a web developer in 2018
Docker tutorials code examples
wifi projects
The repo contains all files of the project of course #1.
FastAPI framework, high performance, easy to learn, fast to code, ready for production