obsidianhydra,Sam Suico,github

I'm currently ...

🌱 self-studying machine learning through a paper by Mehta et al. entitled A high-bias, low-variance introduction to Machine Learning for physicists.
🚀 pursuing an Associate Data Scientist certification on DataCamp.
🔭 picking up Java through the University of Helsinki's MOOC and Coursera's Algorithms, Parts I and II.

🛠️ Tech Stack

Sam Suico's Projects

ap-155-dump

Modules tackled from the Applied Physics 155 class under Ma'am Reinabelle Reyes, PhD and Sir Rene Principe Jr.

ap-157-dump

Computational Analysis and Modeling in Physics taught by Ma'am May Lim, PhD and Sir Louie Rubio.

associate-data-scientist-projects_datacamp

pedagogical projects as part of the Associate Data Scientist Track in DataCamp

image-text-extraction-tesseract

Was supposed to help me pass my PI 100 Finals.

mit-iquhack-2024-classiq-challenge

our attempt on the Classiq Challenge for MIT iQuHACK 2024

ml-for-physicists

Jupyter notebooks for "A high-bias, low-variance introduction to Machine Learning for physicists"

obsidianhydra

repo for personalizing my Github profile

thesis-video

Python script used to generate clips for my undergraduate Thesis using the package Manim

variational-quantum-eigensolver-implemented-on-a-1d-quantum-harmonic-oscillator

Scripts and walkthrough Notebook of my undergraduate thesis entitled "Variational Quantum Eigensolver Implemented on a 1D Quantum Harmonic Oscillator"

Summarizing most of the work needed to learn Variational Quantum Eigensolve (VQE) Very thankful to Koch, D., Wessing, L., & Alsing, P. M. for their tutorial series on Qiskit. Most of this is just me working through papers to try and replicate their results.

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