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.
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Live long and prosper.
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fulcrumapp/csv2table
fulcrumapp/csv2table Public archiveEasily convert static CSV from a web page to a dynamic/searchable dataTable
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St-Pete-Job-Board
St-Pete-Job-Board Public archiveRuby on Rails Job Board - Built during my time at The Iron Yard -
Ruby
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intro-to-haml
intro-to-haml PublicIntro to Haml Meetup held at The Iron Yard in DTSP on 18 Nov 2015
CSS
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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
23**Where should I get the data?**
4To obtain historical hurricane data for training and evaluating your hybrid quantum-classical model, you can consider the following sources:
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99bottles.rb
99bottles.rb 1class Bottles
2def song
3verses(99, 0)
4end
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99bottles.rs
99bottles.rs 1impl Bottles {
2pub fn song(&self) -> String {
3self.verses(99, 0)
4}
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March 2024
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