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所在平台: Udemy |
课程主页: https://www.udemy.com/course/quantum-machine-learning-coding-the-future/
课程评论：没有评论
**课程名称：** 量子机器学习与计算：为未来编程 **课程概述：** 本课程旨在教授量子机器学习（QML）的基础知识，无需量子物理学背景。课程通过编码示例讲解从量子比特（qubits）、叠加（superposition）到张量积（tensor products）等核心概念，从根本上构建学员的理解。即使您曾尝试学习量子计算但感到困难，本课程也承诺提供深入透彻的理解。 课程内容侧重于实际应用，而非需要大量量子比特的传统量子算法。取而代之的是，着重于当前可用的量子机器学习算法。 **课程结构：** 1. **理论基础：** 这是课程最重要的部分，将深入讲解量子计算的关键理论。 2. **量子贝叶斯网络：** 涵盖从随机数生成到概率建模的各种应用。 3. **量子神经网络（QNN）：** 这是课程的核心。将使用 Qiskit 和 PyTorch 进行讲解，并特别展示使用三态量子比特（qutrits）而非量子比特（qubits）构建的 PyTorch 版本量子神经网络。讲师认为，使用三态量子比特能够将量子机器学习推向新的高度。 **核心优势：** * **无需物理学背景：** 理论讲解结合实践编码，易于理解。 * **聚焦实际应用：** 教授当前可用的 QML 算法。 * **前沿技术：** 探索使用三态量子比特（qutrits）构建的量子神经网络，推动 QML 发展。 **等您参与，一起解锁量子计算机在机器学习领域的无限可能！**
Trust me, you don't need to be a quantum physicist to learn quantum machine learning, I wasn't either. That's why in my teaching, I show the theory through coding examples.From qubits to superposition and tensor products, we are going to build the fundamentals from the bottom-up. Even if you have tried before but had a hard time understanding the theory, I guarantee you that this course will give you a thorough understanding of quantum computing. Only the practical stuff are going to be used. This course is not about the typical quantum algorithms which need thousand of qubits, but rather, quantum machine learning algorithms which can be used today. It consists of three sections: First, the theory, which is the most important one. Second, the quantum bayesian networks, which span from random number generation to probabilistic modeling. Finally, quantum neural networks, using both qiskit and pytorch, will be the heart of this lecture.The Quantum Neural Networks are going to be shown with both qiskit and pytorch. The biggest advantage of this lecture is that, the pytorch version of quantum neural networks are going to be constructed using qutrits (rather than qubits), which in my experience, push the boundaries of QML to new heights. So, are you ready to crack the code of machine learning with quantum computers?
