Driven data science and business administration student...
Driven data science and business administration student with experience in web development, machine learning, and data analysis. Seeking to apply skills in programming, data visualization, and front-end technologies to contribute to impactful projects and solve real-world problems. Passionate about using technology and data insights to drive business growth and enhance user experiences while continuing to learn and develop professionally.
StudyPlanGPT
Academic task management with personalized study tips...
StudyPlanGPT allows you to stay on top of your academic tasks with ease. You can write out your assignments, ensuring that nothing slips through the cracks. The app helps you track due dates efficiently, keeping you organized and on schedule. Additionally, it offers personalized tips and recommendations based on your study habits, enabling you to improve your approach to learning. With its advanced features, StudyPlanGPT is designed to enhance your test performance and take your studying to the next level.
Machine learning and Strava data for personalized training...
I am utilizing machine learning algorithms and user data from Strava to provide personalized training recommendations for runners. By integrating a JavaScript backend into an iOS app using Xcode and Swift, I enable real-time running data extraction and presentation to users. This combination of machine learning and real-time data allows for tailored insights that enhance the running experience.
With the volatility of the stock market, this project attempts to use the amount of investors and how this has an influence on the individual stocks, while also calculating the impact of the entire market from past data. Using past data and statistical analysis through many specific models to achieve this goal.
An NLP-based tool that converts unstructured resume data into a structured format, extracting key details like skills, education, and experience to automate candidate screening and improve recruitment efficiency.
his project focuses on distilling large language models (LLMs) into smaller versions and fine-tuning them on domain-specific tasks. The distillation process uses a teacher model (gpt-neo-1.3B) to train a student model (distilgpt2). The model is then evaluated on several NLP benchmarks. Finally, it is finetuned on the Yahoo News Financial dataset and evaluated on FinQA.