Learning Quantum using IBM Qiskit

Following the IBM Qiskit Textbook for learning Quantum Computing - this is just a record for me to have a place to consult for solutions before I reacg out to StackOverflow or Qiskit Slack.

List of lessons I have covered:

• Basic Quantum Circuits
• Superposition & Entangling States
• Parameterized Quantum Circuits
• Data Encoding
• Training Parameterized Quantum Circuits
• Training Parameterized Quantum Circuits (In Practice)
• Quantum Machine Learning
  • Variational Classification (VQC)

Currently

• Quantum Feature Maps & Kernels

Get Started

To get started with the source and notebooks, follow the following steps

1. After cloning this repository; create a virtual environment using Python's venv after doing so, activate the enivornment;

   On MacOS & Unix, run:

   source ./<env_name>/bin/activate

   On Windows, run:

   <env_name>\bin\activate.bat

2. Install all the neccesary pip packages from the requirements.txt file using;

   pip install -r requirements.txt

---

The Jupyter Notebook(s) should detect your kernel and you can run the cells within the notebook(s) and see the ouputs. (I'm using VS Code)