Implementation of basic ML algorithms from scratch in python...

A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum compu…

Simple PyTorch Tutorials Zero to ALL!

Head-start on quantum computing.

This repo contains CUDA-Q Academic materials, including self-paced Jupyter notebook modules for building and optimizing hybrid quantum-classical algorithms using CUDA-Q.

The power of quantum neural networks

Code to accompany: "Measurement-efficient quantum Krylov subspace diagonalisation".

pflotran .in-files for testcases

Materials for my scikit-learn tutorial

Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

Python Data Science Handbook: full text in Jupyter Notebooks

TensorFlow Basic Tutorial Labs

Repo for the Deep Learning Nanodegree Foundations program.

This contains jupyter notebooks with examples for each section which would be quite helful.

Repository for Med2Vec project

scikit-learn interface for quantum algorithms

A Toolkit for Reproducible Study, Application and Verification of QAOA

Materials for the tutorial "Combinatorial Optimization on Quantum Computers"

Bachleor of Science thesis: Using VQE to study LiH and BeH2 molecules.

The codes of my work on the quantum simulation of ground states of Li(+) and Li(2+) ions using QISKIT and PySCF. The algorithm used here is Variational Quantum Eigensolver.