Hello, my name is Daniel Larson. I am a Statistics & Data Science student at UCSB with a passion for sports and music. I hope to integrate my interest in my hobbies and data science into my projects, combining both passions into one career.
- SpiceRack: A web-based application that takes the user's spices in their pantry and outputs recommended recipes accordingly.
- Anti-DUI: A BAC prediction tool powered by regression modeling and Streamlit, aimed at helping students make safer decisions around alcohol— finalist in UCSB’s Project Showcase.
- Mlb_Injury_Report: A pipeline that scrapes the MLB website for player statistics and uses a trained ML model to predict a player's likelihood of injury based on previous game data.
- Spotify Playlist Analyzer: A full-stack web app that creatively assesses emotional tone based on Spotify playlist content — integrating Python, Flask, and the Spotify Web API.
- GUI Automation Toolkit: Built a custom link scraper using PyAutoGUI for platforms with limited automation access
Currently diving deeper into:
- Improving my skills in the languages I know
- Regression and modeling
- Optimal data visualization practices
- API integration and full-stack development
- SQL querying and relational data analysis
- Languages: Python, R, SQL, C++
- Libraries: pandas, NumPy, matplotlib, scikit-learn
- Tools: Jupyter Notebook, Git, GitHub, VS Code, Flask, Streamlit
- Soft Skills: Communication, adaptability, team collaboration
I’m actively seeking data science internships where I can apply my skills in a fast-paced, mission-driven team. Feel free to check out my GitHub github.com/laniel123 or reach out directly on LinkedIn.
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