Books
Hands-On Quantum Machine Learning With Python
First Editions
You're interested in quantum computing and machine learning...
...But you don't know how to get started? Let me help!
Whether you just get started with quantum computing and machine learning or you're already a senior machine learning engineer, Hands-On Quantum Machine Learning With Python is your comprehensive guide to get started with Quantum Machine Learning — the use of quantum computing for the computation of machine learning algorithms.
The first editions of Volumes 1 + 2 are available now. These are more than 800 pages of content that will guide you through the basics of quantum computing and machine learning.
Volume 1: Getting Started

- Basic and advanced machine learning techniques
- Quantum computing introduction
- Parameterized quantum circuits
- Variational hybrid quantum-classical algorithms
- Lots of examples
Volume 2: Combinatorial Optimization

- The Variational Quantum Eigensolver (VQE)
- Various solution ansatzes
- Running algorithms on real quantum computers
- Quantum error mitigation
- The Quantum Approximate Optimization Algorithm (QAOA)
Second Editions - Early Access
Since I published the first two volumes of Hands-On Quantum Machine Learning With Python in 2021 and 2022, the field of quantum machine learning has evolved significantly.
- IBM released Qiskit 1.0 with major API changes. Because the book uses Qiskit extensively, many parts of the first editions require updates.
- IBM also made their 100+ qubit quantum computers available to the public, enabling runs on real hardware that can’t be simulated classically.
- Progress in error-correction and error-mitigation pushes us toward quantum utility: quantum computers become a viable alternative for certain tasks.
Volume 1: Quantum Advantage in Machine Learning

- Basics of Quantum Information
- Quantum Bayesian Networks
- Quantum Support Vector Machines
- Grover's search algorithm
Volume 2: Real World Applications

- Variational Quantum Eigensolver
- Quantum Approximate Optimization Algorithm
- Quantum Error Mitigation
- Running circuits on real devices
Volume 3: Predicting The Future

- Quantum Phase Estimation
- Quantum Fourier Transform
- Shor's algorithm
- Quantum Principal Component Analysis
Volume 4: Toward Artificial General Intelligence

- Pattern Recognition
- Solution space search
- Automated Reasoning
- One-shot learning