Why Fullstack Development?

I had prior experience with front-end development, but I always harbored a curiosity about the inner workings of applications. This curiosity eventually led me to delve into back-end programming. When tasked with a group project during my bachelor's studies, I saw it as the perfect opportunity to embark on a full-stack application journey with my friends. As we collaborated on the project, we absorbed a wealth of knowledge. This experience deepened my appreciation for full-stack development, as it allows you to understand the fundamental mechanics of an application, not just its front-end aesthetics. While I may not have extensive experience with full-stack apps, I take pride in the ones I've worked on and would gladly embrace future opportunities in this domain.

TeSteps (Test+Steps)

TeSteps represents a full-stack social networking project created by my friends and me for a presentation. The project offers all the standard features found in typical social networking sites. However, what set TeSteps apart was a mock test system. Within this system, user responses were evaluated against ideal answers, and users received grades based on the similarity of their responses to these ideal solutions. This blend of social networking and educational elements made TeSteps a distinctive and engaging project.

Face-it

Face It is a comprehensive full-stack web application designed to detect faces in images. The app is built using cutting-edge technologies, with React for the front end, Node.js for the backend, and Postgres SQL for data storage. Leveraging the power of machine learning, Face It integrates with the Clarifai face detection API to provide accurate and efficient face detection in uploaded images.

Leafio

Leafio is a full-stack mobile app for detecting plant leaf diseases. Users can upload images of their plant leaves, and the app takes care of properly scaling them. These images are then sent to our server with a powerful Convolutional Neural Network (CNN) trained to spot leaf diseases. The CNN examines the image, identifies any issues, and quickly sends the results back to the Leafio app. The app efficiently parses the response and presents the results to the user in a user-friendly format, providing them with valuable insights into the health of their plants.

Future Thoughts

My experience with these projects has been incredibly fulfilling, reinforcing my passion for full-stack application development. It's allowed me to gain a comprehensive understanding of how an app comes together, from the user-facing frontend to the backend infrastructure responsible for data management and processing. The way these two important parts of app development fit together has been fascinating and fun. I'm looking forward to doing more full-stack projects because I really enjoy combining technical knowledge with hands-on work.