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  • Pensacola
  • 14:12 (UTC -05:00)

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Achievement: Pair ExtraordinaireAchievement: QuickdrawAchievement: Pull Sharkx3Achievement: YOLO

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jakeroseboro/README.md

Hi 👋, I'm Jake

Software Engineer

  • 🌱 I’m currently working on an open source, cookie-free analytics platform that acts as an alternative to Google Analytics. The technologies being used are C#, ASP.NET Core 7, MediatR, SignalR, NPGSQL, EF Core, NextJs, TypeScript, and Supabase.

  • 👨‍💻 All of my projects are available on this github.

  • 💬 Ask me about C#, Dotnet, NextJs, TypeScript, or General programming questions.

  • 📫 How to reach me: You can message me on LinkedIn

  • 📚 Books I'm Currently Reading: The Beautiful and Damned - F. Scott Fitzgerald

  • ⚡ Fun facts: I am into music production, I love the great outdoors, and I am almost always working on some sort of side project.

Connect with me:

jacobroseboro

Languages and Tools:

photoshop photoshop illustrator mysql javascript react bootstrap git css3 html5

GitHub Stats GitHub Stats


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  1. stellatatech/NetVitals stellatatech/NetVitals Public

    NetVitals is a command line application built to monitor networking speed and collect information about the local network configuration

    C#

  2. heart-disease-ml-api heart-disease-ml-api Public template

    This is a machine learning project built in Python/Flask. It uses SkLearn's random forest classifier to predict the probability of heart disease based on medical history input. The API is hosted on…

    Python 2

  3. heart-disease-prediction-front-end heart-disease-prediction-front-end Public

    TypeScript

  4. WGUPS WGUPS Public

    This is a Python project I made for a Data Structures and Algorithms class. It features a custom hash map used without libraries and uses nearest neighbor to find the quickest package route

    Python

  5. Stock-Prediction-Api Stock-Prediction-Api Public

    This is a Flask API that takes in stock data based on a ticker query and outputs the predicted closing price of the stock for the next day. The prediction is done with sklearn random forest regress…

    Python 1