Hi! I’m a developer who is passionate about building intelligent, user-friendly applications that combine AI, data science, and great design. I also have a strong creative background in music production and graphic design.
Hi! I’m a developer who is passionate about building intelligent, user-friendly applications that combine AI, data science, and great design. I also have a strong creative background in music production and graphic design.
I made a tech support AI chatbot that uses PySide6 for the window, and is powered by Ollama and DeepSeek. It provides a smooth chat experience and is very knowledgeable, and has features that improve the UX such as light mode and dark mode, typing animations, and markdown-formatted AI responses. It also gives users the option to be able to switch models, where for example, they could switch to something like mistral:7b, which would run entirely locally and therefore guarantee confidentiality.
It also handles various edge cases, such as:
You can view this project here.
I made a lead scoring and marketing automation system in order to help sales teams prioritize high-value leads and optimize follow-up campaigns, through the combination of data science techniques, machine learning and process automation to simulate a realistic marketing workflow. The project combines predictive modeling with operational scheduling logic to generate a complete lead engagement plan.
I used logistical regression, data normalization and dynamic weighting in order to determine lead scores, and then was able to create actionable solutions based off of this data, including personalized follow-up timelines and promotional scheduling.
You can view this project here.
I created an app using PySide6 that analyzes recipe data from a dataset called TidyTuesday. It analyzes recipe data in a CSV file with 14,000 recipes, and will recommend recipes to the user based off of the ratings and reviews of those recipes, and will also personalize the recommendations to the user based off of their saved recipes and which recipes they view. It uses a Bayesian rating system and keyword boosting to accomplish this. It also has features that boost the UX including:
You can view this project here.
