This ongoing project focuses on real-time API metrics analytics. Utilising Rust, Apache Kafka, and Apache Druid, it ensures high performance and scalability. The frontend, built with Vue, offers a dynamic dashboard for visualising and analysing collected data, facilitating insightful and actionable analytics
Initially developed in Java, is now being ported to Rust. The solution allows QR codes generation to be blazingly fast and have minimal resource consumption, thanks to the efficiency of Rust, custom QR engine and optimised SVG format. Additionally, it offers customisable templates, enabling personalised and visually appealing QR codes.
This project employs Spring to connect to the Coinbase websocket, enabling real-time monitoring. By listening to the websocket feed, it records and outputs the top 10 levels of bid and ask prices, providing up-to-the-minute market data. This solution is designed for efficient and responsive data handling.
This project leverages PyTorch to train a neural network capable of identifying 102 species of flowers from a given dataset. The challenge involves applying machine learning techniques to develop an accurate and efficient image classifier, demonstrating expertise in deep learning and neural network training.