Stock-Prediction-using-Microservices
● Built a node.js dashboard displaying past and future anticipated stock trends using four coupled microservices, each microservice having its own load balancer and independent execution environment.
● Utilized support vector regression (SVR) and linear regression (LR) models to predict next 30 days future stock trends and obtain a confidence score of 92.9%
● Dockerized the microservices (API, DB, UI, Prediction) and deployed on Google Kubernetes Engine (GKE) and utilized Horizontal Auto Scaling and load balancing feature to increase efficiency by 90%