Skip to content
View ria-123's full-sized avatar
2 followers · 2 following

Block or report ria-123

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don't include any personal information such as legal names or email addresses. Markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
ria-123/README.md

Hi, I'm Ria! 🎓 Computer Science & Statistics student 🔭 Machine learning enthusiast, full-stack developer, and Break Through Tech AI Fellow @ MIT image

I enjoy using machine learning, data analysis, and web development to build real-world projects that make an impact. I’m passionate about growing both technical and leadership skills — from tutoring computer science and leading the CS Club at Suffolk to building deep learning models and generative AI apps. Right now, I’m focusing on refining my ML skills, exploring deep learning, and creating projects that bridge data, design, and user experience. I’m excited to keep learning, collaborating, and hopefully join an internship where I can apply these skills to solve meaningful problems.

🎯 Featured Project: Predicting National Happiness What I Did: Built a regression model to predict Life Ladder scores using the World Happiness Report data Tools: Python, pandas, scikit-learn, Random Forest Result: Achieved ~0.89 R² by selecting top features, helping highlight which social and economic factors most impact happiness See the project here: https://github.com/ria-123/BreakthroughtecheCornellPortfolio

🛠 Tech Stack Languages: Python, Java, JavaScript, HTML, CSS Frameworks & Tools: React.js, Next.js, Tailwind CSS, Node.js, Express.js, Google Maps API, OpenAI API, Bash Data & ML: pandas, scikit-learn, deep learning basics (CNNs) Dev & Platforms: Git, GitHub, Docker, Linux, Google Colab, Firebase

🚀 Projects Skin Cancer Detection with Deep Learning Developed a CNN model for image classification to help detect skin cancer Learnings: Deep learning workflows, dataset preprocessing, and model evaluation

idontknowwheretorent Web app using React, Tailwind CSS, Google Maps API, and generative AI to show rental insights Learnings: API integration, caching for performance, and designing user-focused interfaces

Block-in Chrome extension that blocks distracting sites during focus hours by integrating Google Calendar Learnings: Frontend scripting, extension security, and improving productivity through tech

📫 How to Reach Me 📧 Email: [email protected] 🔗 LinkedIn: linkedin.com/in/riachudasama 💻 GitHub: github.com/ria-123

Pinned Loading

  1. BreakthroughtecheCornellPortfolio BreakthroughtecheCornellPortfolio Public

    Jupyter Notebook of Final Project of Machine Learning Course

    Jupyter Notebook 1