Angle encoding. PennyLane provides built-in support for angle encoding via the AngleEmbedding function. Below is a Python example demonstrating angle encoding for a randomly generated real vector.

Inside this book, you will learn the basics of quantum computing and machine learning in a practical and applied manner. Hands-On Quantum Machine Learning With Python provides a no-nonsense teaching style guaranteed to cut through all the cruft and help you master Quantum Machine Learning.

The notebooks cover a variety of topics to build understanding of parameterized circuits, data encoding, variational algorithms etc., and in the end the ultimate goal of machine learning - how to build and train quantum ML models for supervised and unsupervised learning.

This tutorial provides a comprehensive introduction to the latest developments in quantum machine learning, specifically designed for readers with expertise in machine learning.

This repository contains materials on Quantum Machine Learning and other quantum computing topics, as well as Python code demos using PennyLane, a cross-platform Python library for differentiable programming of quantum computers.

Apr 26, 2024 · In this blog post, we’ll explore the concept of angle encoding and demonstrate how to implement it using Qiskit, IBM’s open-source quantum computing framework. Rotation gates, such as the Rx,...

In this tutorial, each chapter provides a theoretical analysis of the learnability of QML models, focusing on key aspects such as expressivity, trainability, and generalization capabilities.

Throughout the book, there are Python implementations of different Quantum machine learning and Quantum computing algorithms using the Qiskit toolkit from IBM and Cirq from Google Research. Machine Learning enthusiasts and engineers who want to quickly scale up to Quantum Machine Learning.

Jul 13, 2021 · Inside Hands-On Quantum Machine Learning With Python, you’ll learn the basics of machine learning and quantum computing. You’ll learn how to create parameterized quantum circuits and variational hybrid quantum-classical algorithms that solve classification tasks.

Mar 3, 2025 · Quantum Machine Learning (QML) represents a convergence of quantum computing and machine learning, offering new approaches to solving complex problems in data analysis, optimization, and pattern recognition.