Camp QMIND 2021

Getting Started

Step 1: Forking

First you want to create a fork (local copy) of this repository in your own account. Click the button at the top right and select your account.

Step 2: Cloning

On your own fork, clone the repository to your computer. You can find the address in the green code button as shown below.

Now on your computer it's time to use git. Make sure you have git installed on your computer. You should be running all commands in the git terminal. Open a git terminal, navigate to the folder you want the repository downloaded to (using the cd command), and run:

git clone [the repository URL from the image above]

Then enter the repository by running:

cd CampQMIND2021

Step 3: Creating a Virtual Environment and Installing Dependencies

A virtual environment is a way of managing dependencies in Python. Insteal of installing them to your computer, you install them to your project's virtual environment. We have included a file requirements.txt that lists all dependencies. We will use this file to setup our project.

Step 3.1: Without Anaconda

First you need to create a virtual environment. This can be done by running:

python -m venv env

Now activate it:

source env/Scripts/activate

Check you are in the virtual environment by running the following command and making sure it prints (env) at the end:

pip -V

And finally, install your dependencies by running:

pip install -r requirements.txt

Step 3.2: With Anaconda

For Anaconda, all commands should be run in the Anaconda Prompt instead of the git terminal.

First you need to create a virtual environment. This can be done by running:

conda create --name env python=3.8

Now activate it:

conda activate env

You should now see (env) to the right of the command line.

And finally, install your dependencies by running:

conda install --file requirements.txt

Workshop Streams

Slot	Coding	Data Science	DT
1	Intro to Python (Nathan)	ML / Data Science Tools Review (Adam Farley)	DT Intro (Matt Wright)
2	Crash Course on Git / GitHub (Sean Sutherland)	Feature Engineering (Mimi)	Quantum Cryptography (Spencer Hill)
3	Working with Datasets (Griffin)	Sourcing data, web-scraping, etc. (Adam Farley)	Grover's Algorithm (Paul Santilli)
4	Working / Communicating in a Team (Ariana)	Working / Communicating in a Team (Ariana)	Working / Communicating in a Team (Ariana)
5	Overview of ML Algorithms (Ethan Callanan)	Computer Vision (Daniel Stewart)	Decentralized Voting System (Bhavan)
6	Starting a Project + Picking a Model (Adam Farley)	Starting a Project + Picking a Model (Adam Farley)	Decentralized Auction (Mustafa)