Skip to content
View MaryAyobami's full-sized avatar

Block or report MaryAyobami

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
MaryAyobami/README.md

Hi 👋, I'm Mary A. Ogunmola

I have a keen interest in systems, cloud computing and security.

  • 📝 Alongside coding, I have a talent for breaking down complex technical terms through technical writing.

  • 📫 Reach me at ogunmolamaryayobami@gmail.com

Connect with me:

blessedwithjoy_ https://www.linkedin.com/in/mary-ayobami-8a85141b0/

Languages and Tools:

aws azure circleci css3 docker express git go html5 javascript jenkins kubernetes linux mongodb mysql nodejs oracle react reactnative tailwind

maryayobami

Pinned Loading

  1. Microservice-API Microservice-API Public

    This project operationalizes a Machine Learning Microservice API.

    Shell

  2. Udagram-Image-Filtering Udagram-Image-Filtering Public

    This project provides a Node.js-based microservice that allows users to filter images by applying simple filters.

    TypeScript

  3. CalendaPlus-App CalendaPlus-App Public

    Deployment of a 3-tier Application on Azure

  4. Aws-Serverless-Ecommerce-Platform Aws-Serverless-Ecommerce-Platform Public

    Forked from aws-samples/aws-serverless-ecommerce-platform

    Serverless Ecommerce Platform is a sample implementation of a serverless backend for an e-commerce website.

    Python

  5. Detection-of-cyberattack-using-machine-learning-technique-in-networks Detection-of-cyberattack-using-machine-learning-technique-in-networks Public

    Forked from Shiva733/Detection-of-cyberattack-using-machine-learning-technique-in-networks

    Detection of attacks

    HTML