I'm Aakash Kumar, a passionate software developer and machine learning enthusiast. Welcome to my GitHub profile, where you can explore some of my exciting projects and contributions.
- Bachelor of Technology in Computer Science & Engineering, Minor in Full Stack
- Lovely Professional University, Punjab, India
- August 2018 – August 2022
- June 2022 – Present
- Bengaluru, India
At Clover Bay Technologies, I've been working on the development innovative e-commerce platform. I've been involved in designing and implementing microservices, asynchronous APIs, and Kafka consumers using technologies like Reactive Spring Boot, Couchbase, Kafka, and Redis. Additionally, I contributed to building a multi-tenant environment using Spring Boot REST APIs and MySQL integration to securely store hotel booking data. Through API automation, we successfully replaced a manual process, saving valuable time and reducing errors.
- August 2021 – May 2022
- Bhubaneswar, India
As a Machine Learning Intern at Highradius Corporation, I worked on developing a payment prediction model using various algorithms like random forest and XGBoost. The model aimed to improve cash flow management by accurately forecasting payment dates. I utilized Python libraries such as Pandas, NumPy, Seaborn, and Matplotlib for data analysis and visualization.
- March 2023
In this project, I developed a real-time microservices application using Spring Boot, Spring Cloud, Netflix Eureka, API Gateway, Keycloak, Resilience4j, and Kafka. The application leverages service discovery with Eureka, efficient routing with the API Gateway, and secure authentication and authorization with Keycloak.
- August 2021
I developed an AI-enabled B2B invoice management system using Java Servlet, Python, MySQL, HTML, CSS, JavaScript, and Jquery. This system utilized regression models for data prediction, achieving an impressive mean squared error (MSE) of 10. The user interface features pagination, editable fields, and grid row manipulation.
- May 2020
For movie enthusiasts, I developed a recommendation system using Python and the sci-kit-learn library. The system suggests new movies based on their similarity to a user's favorite films. The recommendation engine scraped data from IMDB and utilized cosine similarity for movie score calculation. I also implemented a user-friendly GUI for an interactive experience.
- Languages: Java, Python, C/C++, SQL (Postgres, MySQL), JavaScript, HTML/CSS, distributed NoSQL cloud databases
- Frameworks: Spring Boot, FastAPI, Sanic, Apache Kafka, React, Node.js, Flask, JUnit, Material-UI
- Developer Tools: Git, Docker, IntelliJ, VS Code, PyCharm, AWS
- Libraries: pandas, NumPy, matplotlib
Feel free to reach out to me via email at aakashkumar2001jha@gmail.com or connect with me on LinkedIn. You can also explore my personal website at
Thank you for visiting my GitHub profile. Happy coding! 🚀