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Achievements

Achievement: YOLOAchievement: Pull Sharkx2Achievement: QuickdrawAchievement: Arctic Code Vault Contributor

Achievements

Achievement: YOLOAchievement: Pull Sharkx2Achievement: QuickdrawAchievement: Arctic Code Vault Contributor

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justinliu23/README.md

AI Projects AI Projects   LinkedIn LinkedIn

Hey!

My name is Justin Liu. Thanks for stopping by to check out my projects 😄

AI Engineer and Researcher

Specializing in data science and AI research over the last five years, I’ve come to appreciate the surprisingly synergistic relationship between academic and production environments. My research knowledge has enabled me to have a deep understanding of machine learning methods and build end-to-end solutions in computer vision, NLP, and agent-based systems.

About me

  • 📚 Harvard sophomore pursuing a concurrent AB/SM in CS with a minor in Stats
  • 🌱 Builder + investor backgrounds in B2B SaaS/Fintech
  • 👨‍💻 Currently building AI Agents withconcierge.ai
  • 🛠️ Hackathon enthusiast and organizer of YouthHacks [website] [devpost]
  • 🎨 I like to draw :) [fine art portfolio]

Connect

Always looking to collab so feel free to shoot me a message!

Pinned Loading

  1. transformer-from-scratch transformer-from-scratch Public

    Implemented and optimized a Transformer network using custom encoder/decoder layers

    Jupyter Notebook

  2. real-time-object-detection real-time-object-detection Public

    Prototype of Real-Time Object Detection System for Self-Driving Cars

    Jupyter Notebook

  3. baidu-stock-pitch-ml baidu-stock-pitch-ml Public

    Supporting statistical analyses, price forecasting, and economic research for Baidu (BIDU) stock pitch

    Jupyter Notebook

  4. Proximity Proximity Public

    Forked from timobraz/proximity

    HackMIT 2023

    HTML

  5. spotify-data-analytics spotify-data-analytics Public

    Exploring Music Trends: Machine Learning and Visualizations with Spotify Data

    Jupyter Notebook

  6. facial-recognition-system facial-recognition-system Public

    Solving the 1:K matching problem with one-shot learning and the triplet loss function

    Jupyter Notebook