Skip to content
View tgaeta's full-sized avatar
🖖
Live long and prosper.
🖖
Live long and prosper.
Block or Report

Block or report tgaeta

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
tgaeta/README.md

I'm Tony. I have a passion for software engineering, photography, and the wonders of the cosmos. At present, I'm diving deep into Rust and exploring cutting-edge web technologies like Next.js, Solid.js, SvelteKit, Qwik, Astro, Tauri, Bun, DALL-E 3, Github Copilot, and OpenAI's GPT-4.

Pinned Loading

  1. job_tracker job_tracker Public

    Efficiently manage and track your job application history

    Ruby 5 1

  2. Comprehensive Rails Developer Guide.md Comprehensive Rails Developer Guide.md
    1
    # Comprehensive Rails Developer Guide
    2
    This comprehensive guide covers the progression from Junior to Principal Rails Developer, providing detailed explanations and code examples for each skill level. It serves as a roadmap for developers looking to advance their Rails expertise and tackle increasingly complex challenges in web application development.
    3
    
    
    4
    ## Table of Contents
    5
    1. [Junior Rails Developer](#junior-rails-developer)
  3. fulcrumapp/csv2table fulcrumapp/csv2table Public archive

    Easily convert static CSV from a web page to a dynamic/searchable dataTable

    JavaScript 6 5

  4. St-Pete-Job-Board St-Pete-Job-Board Public archive

    Ruby on Rails Job Board - Built during my time at The Iron Yard -

    Ruby

  5. Explore the development of a hybrid ... Explore the development of a hybrid quantum-classical model for hurricane forecasting, devised by GPT-4 through an intricate question-answer chain. This comprehensive guide covers the essential steps in a technically precise yet comprehensible manner, from choosing an appropriate classical machine learning model to incorporating quantum optimization algorithms and integrating quantum-enhanced sampling techniques. Gain insights into testing and refining the model using quantum simulators and real quantum hardware. Experience the synergy of machine learning and quantum computing, as it elevates the accuracy and efficiency of hurricane trajectory and intensity predictions.
    1
    # Developing a Hybrid Quantum-Classical Model for Hurricane Forecasting: A Comprehensive Guide
    2
    
    
    3
    **Where should I get the data?**
    4
    To obtain historical hurricane data for training and evaluating your hybrid quantum-classical model, you can consider the following sources:
    5
    
    
  6. intro-to-haml intro-to-haml Public

    Intro to Haml Meetup held at The Iron Yard in DTSP on 18 Nov 2015

    CSS