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FasiTech

Hi, I'm Fasi

Full Stack Developer

I'm a web developer dedicated to building responsive, and user-friendly experiences on the web.

About Me

Hey, I'm Fasi, a full stack developer who genuinely enjoys turning ideas into real, working web experiences. I’ve always been curious about how things work behind the scenes, and that curiosity naturally led me into the world of development. Over time, I found myself falling in love with the process of building user-friendly frontends with React to crafting solid backends using Node.js and MongoDB. I’m passionate about solving real problems with clean, scalable code and always eager to learn something new.

I’ve completed a full stack development course, but for me, learning is something that never really stops. I spend a lot of time experimenting with new tools, reading docs, and building side projects just for fun. My long-term goal is to explore areas like Artificial Intelligence and Machine Learning, while continuing to grow as a developer and creative thinker.

TOTAL PROJECTS

Innovative web & mobile solutions crafted

08

CERTIFICATES

Professional skills validated

02

TECHNOLOGIES

Worked with 20+ tools and frameworks

20+

Technical Stack

Technologies and tools I use to build innovative solutions

My Projects

Employee Attendance Register

Employee Attendance Register is a full-stack web application designed to simplify the management and tracking of employee attendance. It allows administrators to easily add employees, monitor attendance records, and ensure the security of employee data.

Website GitHub

Stress Detection System

Stress Detection System, a smart web application that predicts a person's stress level based on their sleep-related health indicators. Designed with a clean, modern UI using Bootstrap, this tool uses machine learning to promote awareness and well-being.

Website GitHub

Task management

The Task Management Web App is a smart productivity solution designed to streamline planning and execution. With an AI-powered scheduler, it automatically prioritizes and organizes tasks based on time and importance. Developed with Next.js, Clerk, and MongoDB, and powered by the Google Gemini 2.5 API, the app combines modern web technologies with artificial intelligence to deliver an efficient and user-friendly experience.

Crime Prediction System

Crime Prediction System leverages a Bidirectional Convolutional LSTM (biConvLSTM) Autoencoder model to forecast the likelihood of criminal activity based on historical patterns. Focused specifically on cities within Hyderabad, the system uses a dataset of over 40,000 crime records to learn temporal and spatial trends

GitHub

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