Faris Nizamani

As a Computer Science student at FAST University, I have developed a strong foundation in full-stack web development, machine learning, and data analysis. My hands-on experience includes an internship at ORL Private Limited, where I contributed to front-end development using React.js, HTML, CSS, and JavaScript. I take pride in building responsive user interfaces that enhance user engagement and collaborating with remote teams to integrate UI components effectively.

Throughout my academic journey, I have worked on various projects that showcase my skills in machine learning and data science. Notable projects include an image classification model using VGG16, where I implemented techniques to combat overfitting and achieved robust accuracy. Additionally, I developed a linear regression model for predicting house prices and conducted an analysis of university enrollment trends using Python libraries for data cleaning and visualization. I am passionate about leveraging technology to solve complex problems and build efficient, scalable solutions.