https://github.com/agnostiqhq/tutorials_covalent_qsite_2022

Covalent tutorial for Q-Site conference 2022
https://github.com/agnostiqhq/tutorials_covalent_qsite_2022

agnostiq covalent covalent-tutorial machine-learning qsite2022 qsvm quantum quantum-computing quantum-machine-learning quantum-workflow svm

Last synced: 15 days ago
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Covalent tutorial for Q-Site conference 2022

• Host: GitHub
• URL: https://github.com/agnostiqhq/tutorials_covalent_qsite_2022
• Owner: AgnostiqHQ
• Created: 2022-10-11T02:05:06.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2023-08-14T23:10:02.000Z (over 1 year ago)
• Last Synced: 2024-11-17T08:25:44.708Z (3 months ago)
• Topics: agnostiq, covalent, covalent-tutorial, machine-learning, qsite2022, qsvm, quantum, quantum-computing, quantum-machine-learning, quantum-workflow, svm
• Language: Jupyter Notebook
• Homepage:
• Size: 2.34 MB
• Stars: 2
• Watchers: 10
• Forks: 0
• Open Issues: 12
• Metadata Files:
  • Readme: README.md

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README

        
# Q-SITE 2022: Covalent QML Tutorial







This repository contains all the material needed to complete the `covalent` tutorial and challenge exercises presented at *Q-SITE 2022* (University of Toronto).

Here, you'll find:

1. The slides from the talk (`slides.pdf`).

2. Jupyter notebooks containing the tutorial (`tutorial/covalent_qsvm_tutorial.ipynb`) and challenge (`exercise/covalent_qsvm_challenge.ipynb`) scripts.

## Install instructions

To run the jupyter notebooks, you will need a Python (`conda`) environment with the requisite dependencies.

* First, clone or download this repository to your local machine.

* If you don't already have conda, navigate to [the conda download page](https://conda.io/projects/conda/en/latest/user-guide/install/download.html) and install a version of either Miniconda or Anaconda compatible with your OS. This is strongly recommended over using the 'system' Python.

* To create a fresh conda environment, navigate to root directory of this repo (`tutorials_covalent_qsite_2022`) and run

        conda env create -f environment.yml

    This will create an environment called `qsite_covalent`.

    

* To use this environment, activate it with the following command:

        conda activate qsite_covalent

* You can make the environment visible to your Jupyter Notebook viewer by running

        python -m ipykernel install --user --name=qsite_covalent

    Jupyter notebooks can be opened with

        jupyter notebook 

    With the notebook open in a browser window, select the kernel (i.e. Python environment) from the 'Kernel' drop-down menu:

    

    > Kernel > change kernel > select qsite_covalent

Alternatively, you can skip the `ipykernel install` command by opening notebooks with the `qsite_covalent` environment already activated. You'll have to do this every time, so the above method is perhaps more convenient.

## Start Covalent

After successfully creating the conda environment, the Covalent server can be started as follows

        covalent start --ignore-migrations

Covalent can optionally be started in debug mode for more verbose logging as follows

        covalent start -d --ignore-migrations

That's it, you are good to go!