|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/quantummachinelearning/
课程评论：没有评论
课程名称：实践量子机器学习 课程概述：该课程是一个实用的入门课程，旨在弥合经典机器学习与量子计算之间的差距，赋予学员工具、理论和实践洞察，以开始他们在量子机器学习（QML）领域的探索。无论你是好奇的学习者、数据科学家，还是研究前沿技术的研究人员，这门课程将引导你了解QML的基本概念及其在实际问题中的应用。 通过结合可视化、互动练习和实践评估，你将学习量子电路如何进行计算，探索基础量子算法，并发现这些算法如何优化以应对现实世界中的应用，例如分类、回归、图像处理和分割。此外，学员还将获得Ingenii的Python库的独家访问权限，用于可视化和优化量子算法，使量子开发变得更加直观和易于理解。 课程结合了我们原有的QML基础和医学影像课程的内容，并受到即将发布的量子中心开发资源的学习方法启发，将六个深入的应用导向章节整合成一门完整的入门QML课程。加入超过600名已经开始他们量子机器学习之旅的数据科学家、学生和教育者，开启你的学习之旅。
This hands-on introductory course is designed to bridge the gap between classical machine learning and quantum computing, empowering you with the tools, theory, and practical insights to begin your journey into quantum machine learning (QML). Whether you're a curious learner, a data scientist, or a researcher exploring cutting-edge technologies, this course will guide you through the fundamental concepts of QML and how they can be applied to real-world problems.Through a combination of visualizations, interactive exercises, and hands-on assessments, you'll learn how quantum circuits perform computations, explore foundational quantum algorithms, and discover how quantum algorithms can be optimized for real-world applications such as classification, regression, image processing, and segmentation.You'll also gain exclusive access to Ingenii's Python library for visualizing and optimizing quantum algorithms-designed to make quantum development more intuitive and accessible. By the end of the course, you'll have a solid understanding of quantum machine learning fundamentals and the skills to apply them to practical, impactful challenges.Expanding on our original QML Fundamentals and Medical Imaging courses, and inspired by the learning methods in our upcoming Quantum Hub development resource, this Udemy course combines six, in-depth, application-focused chapters into a complete introductory QML course.Join over 600 data scientists, students, and educators who have already started their Quantum Machine Learning journey.
