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A machine learning engineer leverages programming and statistical expertise to design, implement, and deploy predictive models. They bridge the gap between data science theory and practical applications, solving real-world problems through innovative machine learning solutions.
These projects as a part of my Data Science internship involve data visualisation, analysis, & prediction using various datasets and machine learning techniques. They utilize libraries like pandas, matplotlib, seaborn, scikit-learn, and NLTK for tasks ranging from gender and age visualisation to sentiment analysis and decision tree classification.
# PRODIGY_WD_01 Responsive Landing Page - Plant-X - Responsive Plant-Based Landing Page, for a plant-based website, designed and built using HTML, CSS, and JavaScript. This webpage is optimized for various devices and features an interactive navigation menu that changes color when scrolled or hovered over it.
🚀 House Price Prediction Project 🏡 Developed at Prodigy Infotech: Predicting house prices using linear regression on square footage, bedrooms, and bathrooms. Tech Stack: Python, Pandas, Scikit-learn, Matplotlib. Dataset: Kaggle House Prices.
🎮 Tic-Tac-Toe Game ✨ - Built during my Prodigy Infotech internship, this React.js project features an interactive UI for a classic two-player Tic-Tac-Toe game. 🏆 Enjoy real-time winner detection and a seamless user experience using React.js, JavaScript, HTML, and CSS. 🎲👨💻
simple stopwatch ⏲️ application built using React ⚛️ and styled with Tailwind CSS 🎨. Features include start ▶️, stop ⏹️, resume ▶️, and restart 🔄 functionality with real-time updates. Perfect for learning React state management and Tailwind CSS styling.