I am a passionate and driven Computer Science student with a strong interest in Software Development and Data Science using Python, Web Development. With experience in Python, Flask, SQL, and Frontend Software like HTML5, CSS, and JavaScript, I enjoy tackling complex problems and turning ideas into reality through code. Currently, I am working on projects like a portfolio website that showcase my ability to build practical and user-friendly solutions. My goal is to continually expand my skill set and contribute to innovative projects that have a meaningful impact. In addition to my technical skills, I am a strong communicator and enjoy collaborating with teams from diverse backgrounds. I am always eager to learn new things and take on challenges that push me out of my comfort zone. In my free time, you can find me exploring new technologies, contributing to open-source projects, or playing video games like Valorant and Red Dead Redemption 2, reading mystery novels, or listening to music. Feel free to reach out if you'd like to connect or collaborate on a project!
Developed a Machine Learning model to predict income inequality using the Gini Index, analyzing population classes for accurate assessments. This project focuses on understanding socio-economic disparities and offers insights into potential policy implications based on the predicted inequality levels.
A sentiment analysis model is a machine learning model designed to analyze and classify the sentiment expressed in text data. Typically, the model is trained on labeled datasets where the text is associated with sentiments like positive, negative, or neutral. The process involves converting text into numerical features using techniques such as tokenization, embedding, or TF-IDF, and then feeding these features into a classifier like a neural network, logistic regression, or a support vector machine. The trained model can then be used to predict the sentiment of new, unseen text data, making it a valuable tool for applications such as customer feedback analysis, social media monitoring, and movie review classification.
The To-Do List with Voice Recognition is a productivity application that allows users to manage their tasks using voice commands. Instead of manually typing tasks, users can add, edit, and delete tasks by speaking, making the app more intuitive and hands-free. The application leverages speech recognition technology to convert spoken words into text, which is then processed and added to the task list. This innovative feature enhances user convenience, especially in situations where typing is impractical, and provides an efficient way to stay organized.
The Ping Pong game is a simple yet engaging browser-based game created using JavaScript, HTML, and CSS. The game features a classic two-player setup where players control paddles to hit a ball back and forth across the screen. The objective is to prevent the ball from passing your paddle while trying to score against your opponent. The game is visually appealing and interactive, with smooth animations and responsive controls, providing an enjoyable experience for players.
The Hangman game is a movie title guessing game where players try to uncover a hidden movie title by guessing letters within a limited number of attempts.
Speech-to-Text and Text-to-Speech project enables seamless voice-to-text conversion for transcribing spoken words and text-to-voice synthesis for auditory output, enhancing accessibility and communication. It integrates natural language processing and speech synthesis technologies for a user-friendly and efficient experience.