What Is Quantum Machine Learning? | TensorFlow Quantum

The video tutorial introduces classical computing concepts, such as binary code, and contrasts them with quantum computing principles like superposition and entanglement. It discusses the challenges of quantum computing, including decoherence, and the potential for quantum supremacy. The tutorial then focuses on simulated quantum computing using TensorFlow, demonstrating how to build and train a neural network to calibrate qubits. The video concludes with practical examples of training models using quantum circuits.

What is the fundamental difference between classical bits and quantum bits (qubits)?

Explain the concept of superposition in quantum mechanics.

What is quantum supremacy and how was it demonstrated by Google?

Describe the challenges associated with creating quantum computers.

What are the potential implications of quantum computing for machine learning?

What is hybrid quantum classical computing and what problem does it aim to solve?

How does a quantum circuit perform computations?