This is my official portfolio website that shows all the details and work experience.
Download CVI am a passionate and dedicated aspiring Data Scientist in the final year of my Bachelor's degree in Computer Engineering. My journey into data science began with a keen interest in uncovering patterns and insights from complex datasets. Over time, I have honed my skills in Python, SQL, and various data visualization tools, allowing me to transform raw data into actionable insights. I have hands-on experience in building predictive models, conducting exploratory data analysis, and deploying machine learning algorithms to solve real-world problems. My portfolio showcases a range of projects, from analyzing large datasets to developing interactive dashboards. I am committed to continuous learning and am always excited to tackle new challenges in the ever-evolving field of data science.
Python-based face recognition system with a Tkinter GUI for registering and recognizing users. The system allows users to register by capturing images via webcam or by selecting images from local storage. It stores the face data and performs real-time face recognition using a webcam, recording recognized faces into a MySQL database.
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A comprehensive House Price Prediction model using Kaggle's dataset. The project includes data preprocessing, feature engineering, and model development. For visualization, I developed a user-friendly frontend that displays predicted prices and insights into the factors affecting house prices.
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This project analyzes text sentiment and emotions using Python, NLP, and tweet extraction. It preprocesses text, detects emotions via a predefined lexicon, and uses the VADER model for sentiment analysis. Tweets are fetched with GetOldTweets3, and results are visualized with matplotlib. The project utilizes Python, NLTK, GetOldTweets3, and matplotlib for insights into sentiment and emotions in text data.
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A machine learning project that classifies Iris flowers into three species: Iris Setosa, Iris Versicolor, and Iris Virginica. The model was trained using the famous Iris dataset and achieves high accuracy through data preprocessing and model optimization. The project includes visualizations to demonstrate the decision boundaries and feature importance.
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An interactive Bike Sales Dashboard using Excel, based on data from an uncleaned CSV file. The dashboard features charts, pivot tables, and filters to provide clear insights into sales performance and trends.
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An interactive and visually compelling dashboard using Tableau to analyze Airbnb data. The dashboard provides valuable insights into various aspects of Airbnb listings, such as property types, pricing trends, occupancy rates, and geographic distribution.
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A comprehensive dashboard in Power BI to analyze survey data from data professionals. The dashboard provides insights into various aspects such as demographics, job roles, skills, and salary trends. Despite starting with uncleaned data, the dashboard effectively visualizes the key findings from the survey.
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The Anonymous Feedback Platform is a secure web application designed for collecting and sharing anonymous feedback. Users can create profiles, distribute feedback forms, and receive responses while keeping their identities private. The platform is built with Next.js, styled using Tailwind CSS, and leverages MongoDB for database management. TypeScript ensures robust code quality, while NextAuth.js handles secure authentication.
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RetroToons is a nostalgic platform that invites users to revisit their favorite cartoons from childhood while fostering a sense of community among enthusiasts. The website features a vibrant home page where cherished memories come alive, alongside a gallery showcasing beloved classics like Pokémon and SpongeBob SquarePants. Users can explore iconic cartoons from various decades, spanning from the '80s to the 2000s, and participate in a fun quiz to discover which cartoon character they resemble the most. Additionally, the blog section offers insightful articles about legendary shows
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Developed a dynamic anime wallpaper website using HTML, CSS, and vanilla JavaScript. This project allows users to browse and download high-quality anime wallpapers. It features an intuitive interface, responsive design, and functionality to preview images in full screen. This project showcases my skills in front-end development and user experience design.
View on WebI am currently pursuing my Bachelor's degree in Computer Engineering at LDRP Institute of Technology and Research in Gandhinagar, Gujarat.
Completed my schooling upto 10th Std at Uma Vidhyalaya in Himmatnagar,S.K.,Gujarat.
Continued my higher education of 11th & 12th Std at N & K Pandya Himmat Highschool-2 in Himmatnagar,S.K.,Gujarat.
Data Science Intern at Prodigy Infotech-sept 2024
My work involves data cleaning, exploratory data analysis, and the development of machine learning models. Utilizing Python, Pandas, Numpy and Scikit-learn, I create visualizations and predictive models that support marketing and strategic initiatives. certificate