Cloud

People are often scared to learn Kubernetes because it’s difficult to set up an environment to play around with. Sure, you can use a project like minikube to learn on your own, but running it on your laptop seems limited, and you may not get to experience all the awesome features Kubernetes offers (remember, it was born for high availability). Or, if you have money, you can use a managed Kubernetes cluster from one of the cloud providers. Often, they’ve abstracted away so many things under the hood that you only need to learn kubectl and you’re good to go.

This repository contains a complete end-to-end system for real-time credit card fraud detection, including data analysis notebooks, a machine learning API, and infrastructure-as-code for cloud deployment. The system is designed with a modern, observable, and scalable architecture.

I’m the kind of person who will happily spend 10 hours building an automation script just to save 10 minutes of manual work every day. If that sounds like you, you’re in the right place.

This project aims to provide users with a reliable solution to identify counterfeit products. Originally designed as a C2C Ecommerce Platform, the project has evolved to focus solely on counterfeit detection. The system offers two methods for users to verify product authenticity: utilizing a Teachable Machine model and employing a barcode scanner.

Today, I want to share my experience with you about the project I worked on during the Steam Hacks 2023 competition. Although my team did not win any major awards for this project, it was an incredible learning opportunity for me, particularly in terms of coding. Moreover, I also gained valuable insights into the collaborative process through working with my amazing new friend from Son La - Minh Chau.