About the Project

Introduction to Quantum Computing and building some Quantum Machine Learning Algorithms like QNNs, Quantum Regression and Classification, QSVCs, QCNNs.

Resources

Week 0

1. Linear Algebra Refresher: Videos 1-3, 9-11, 13-15 of 3B1B Lin Alg Playlist
2. The Language of Quantum mechanics
3. This video shall provide an intuitive introduction to QM
4. What are wave functions
5. What does a wave function represent

Week 1

1. Lectures 1 to 3 of this playlist
2. Reference notes for the lectures

Relevant Sections of Nielsen Chuang

Link to the book can be found here

1. Start off with Stern-Gerlach (1.5.1). Provides a good understanding of some non-intuitive parts of QM

2. [Highly Recommended for everyone] Cover the results of 2.1

   Linear Algebra. Proofs not important for the project but having an understanding of the results will really help

3. Post that, you can read the first 3 sub sections of 2.2. Anything beyond that would be a it too complex for now.
4. Then, cover 4.1 and 4.2.

Introduction to Python

1. Intro to Python
2. Exception Handling
3. Anaconda
4. Path and environment variables for Python and Anaconda in Windows
5. Interactive Python Notebooks
6. Venv
7. Managing Packages with venv
8. Python virtualenv
9. PyEnv for Python Version Management
10. Git

Week 2