Kevin Valani

Kevin Valani

Software Developer

About Me

I am a developer who creates small, medium and large applications that are written with Python or C# or Java. I have spent the bulk of my time learning these programming languages and technologies, but I'm always excited to learn new technologies.

Specialization

Backend

Python3 Flask
C# WPF & UWP .NET
JavaEE Servlet JSP

Client Side

HTML 5 CSS JavaScript
jQuery Angular
JSON XML Ajax

Server & Clouds

Ubuntu Ngnix Gunicorn GCP
App Engine Compute Engine Cloud Storage

Database & OS

MySQL Oracle SQL PLSQL
MongoDB macOS
Ubuntu Windows 10

Featured Work Experience

oyeStudent.com

Python3.8 / Flask Project

My Contribution for the Project

oyeStudent is one of the well-known student service providers in many cities, but their website was just a static one-page with a little introduction and Google Contact Form. I knew the long-term smart solution of building a dynamic website with Python, Flask, and Databases to transform the working of a company from paper-based to digital and efficiently work and make decisions using the digital data.

For the company, at backend, I developed the Flask Web App using and integrating Flask, MySQL, MongoDB, Payment Gateway API, and several other modern technologies.

For the server, I decided to use Ubuntu 18.04 with Nginx and Gunicorn for better performance, control and security of the app as compared to shared hosting.

This Web App allowed other employees in the company to list products and services online, collect payments as well as automatically send receipts on their and buyers email as well as allowed students to upload their documents, mark sheets, and access receipts on the website under their account.

Because of this Web App, the company provided services trice more as compared to the previous quarter and also decided to expend their presence in 2 more cities.


My Special Contribution for the Project

Developed Machine Learning Models such as Linear Regression and Decision Tree to help company employees make better use of available data to make an accurate and faster decision based on the predictions made by the model. I used Machine Learning tools such as TensorFlow 2.0, scikit-learn, NumPy, and Pandas.