Quantum Machine Learning
This lecture series will take you through key concepts in quantum machine learning, such as parameterized quantum circuits, training these circuits, and applying them with hardware considerations in mind.
Intro to Quantum Machine Learning
Want to learn about this exciting, developing field? If you're familiar with quantum computing basics, this lecture series will give you a primer on machine learning, walk you through key concepts, and bring you up to speed with recent developments.
Suggested Reading
- Qiskit Quantum Machine Learning Course
- Read the Fine Print
- The effect of data encoding on the expressive power of variational quantum machine learning models
- What is the computational complexity of an SVM?
- Supervised learning with quantum-enhanced feature spaces
- Quantum Convolutional Neural Networks
- Quantum implementation of an artificial feed-forward neural network
- Evaluating analytic gradients on quantum hardware
- Barren plateaus in quantum neural network training landscapes
- The power of quantum neural networks
- A generative modeling approach for benchmarking and training shallow quantum circuits
- Dimensionality reduction
- Calibrating Qubits with Qiskit Pulse