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Hi, I'm Sathwik Yarlagadda 👋🏾

Web Dev & Machine
Learning Enthusiast

A passionate computer science student, possessing a keen interest in Fullstack Web Development and a strong aspiration for the exciting world of Machine Learning. Strives to create exceptional user experiences (UI/UX) while exploring cutting-edge technologies.

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About Me

I'm Sathwik Yarlagadda, a computer science enthusiast with a passion for solving puzzles through programming and software development. This passion not only drives my academic pursuits but also shapes my professional projects. My keen interest in machine learning stems from its broad spectrum of problem-solving capabilities, allowing me to explore and address diverse challenges across different fields.

As someone deeply driven by topics that capture my attention, I approach each project with a focus on innovation and precision. My adaptability and meticulous attention to detail ensure that I consistently deliver high-quality and professional work, whether I'm developing sentiment analysis tools or automating cryptocurrency trading. These traits, combined with my commitment to continuous learning and improvement, enable me to consistently produce exceptional results and exceed expectations.


Technologies

  • Python (Advanced, with applications in Web Development and Machine Learning)
  • ReactJS (Development of dynamic user interfaces and SPA)
  • HTML & CSS (Proficient in creating responsive and accessible web designs)
  • Machine Learning with PyTorch & scikit-learn (Building and training advanced models)
  • Cloud Platforms (AWS & Google Cloud including services like EC2, RDS, and Google Cloud Compute Engine)
  • FastAPI & Flask (Designing robust APIs and server-side logic)
  • JavaScript (ES6+ for modern frontend and backend development)
  • SQL Databases (Proficiency in MySQL & PostgreSQL for data management and queries)
  • Cloud Databases (AWS RDS & Google Cloud SQL for scalable database solutions)
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Projects & Contracts

I focus on the practical applications of technology, like developing robust applications, implementing machine learning algorithms, and leveraging data analytics. I tackle challenges through advanced computational methods and data-driven solutions, ensuring each project addresses real-world problems efficiently. These projects showcase my ability to manage complex tasks effectively, from optimizing user interfaces to automating processes, consistently delivering tangible and impactful results.

Wennational Insights

Wennational Insights

Wennational Insights is a React Native mobile app built with Expo to manage bonus data across franchise stores. The app features a user-friendly interface and data visualizations that allows managers to easily navigate and manage bonus information.

The app integrates Microsoft authentication through Supabase for secure logins and dynamic role-based access. It allows users to filter and display bonus information by time, store, area, or district, providing flexibility for targeted data analysis.

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Modern Learning Rate Schedules

Modern Learning Rate Schedules

Exploring Advanced Learning Rate Techniques

This project delves into novel learning rate schedules that enhance the efficiency of gradient descent algorithms. The focus is on experimenting with modern approaches like Chebyshev fractal learning rates, which can accelerate convergence beyond traditional methods.

Through some experiments, this study demonstrates how dynamic adjustments in learning rates can lead to significant improvements in training deep learning models. The results highlight the potential of these modern techniques to optimize performance across a variety of machine learning tasks.

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Graph-Based Credit Card Fraud Detection

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Graph-Based Credit Card Fraud Detection

This project employs Graph Machine Learning techniques to enhance credit card fraud detection. Utilizing GraphSAGE and a novel GNN variant, we analyze transaction networks to uncover fraudulent patterns.

The approach integrates complex transaction data into graph structures, enabling the detection of sophisticated fraud schemes that conventional methods might miss. The results demonstrate the potential of GML in identifying and preventing credit card fraud.

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Tables - Social Media Web Application

Tables Social Media Web Application

Tables - Social Media Web Application

Developed using Flask, this application allows users to post, comment, and influence the community through upvotes and downvotes. But here's the twist: the content moderation system, powered by YOLOS object detection, ensures that no tables are allowed on the platform!

From user profiles showcasing personal posts and editable descriptions to comprehensive post and comment management systems, every aspect of the user experience is designed to be seamless and engaging. Security is also a priority, with file uploads strictly managed to prevent unwanted content, ensuring a safe environment for all users.

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Get In Contact

Whether it's projects or buisness inquiries, my inbox is always open so please feel free to reach out to me and I'll get back to you ASAP!

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