Want to hit the ground running on hackathon day? 

We’re putting together a toolkit of useful resources (quantum computing guides, ML frameworks, datasets, and platform tutorials...) to help you prepare and innovate with confidence. 

Useful links on the the day of the event

Common resources for both tracks

General information

• Basics of Quantum Information

[IBM]

• Qiskit Onboarding Tutorial (Google Colab notebook)

[Quandela]

• Quandela Training Center (browse to the Mil'HaQ Fest module)

Track 1 - Quantum Walk

Quantum Walk Resources

• The Black Scholes model for option pricing (Wikipedia)

• Quantum walk option pricing model based on binary tree

• Implementation of Quantum Walks on IBM Quantum Computers (gate-based approach applicable to Quandela as well)

[IBM]

• Tutorial on Hadamard Quantum Walk by Jun Dai - Easy level (Google Colab notebook)

• Tutorial on Quantum Walk with Qiskit - Expert level (Google Colab notebook)

[Quandela]

• Quantum Random Walk implementation using photonic quantum computing

Track 2 - Quantum Machine Learning

AI and Quantum Machine Learning Resources

• AI for financial forecasting

• Quantum Reservoir for financial forecasting

• A study on the form of weighted networks

• Bringing Machine Learning to Quantum Computers

[IBM]

• QML with Qiksit

• Tutorial on quantum reservoir using Qiskit (Google Colab notebook)

[Quandela]

• MerLin Tutorial (Google Colab notebook)

• PyTorch Tutorial (Google Colab notebook)

• Implementation of quantum reservoir using Quantum Machine Learning

⚡More about Machine Learning

🚀 To join The Mil'HaQ Fest community