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所在平台: Udemy |
课程主页: https://www.udemy.com/course/artificial-intelligence-optimization-algorithms-in-python/
课程评论：没有评论
课程名称：人工智能：Python中的优化算法 课程概述： 你心目中的“最佳世界”是什么样的？人们会相处得更好吗？交通会更快吗？我们会更好地照顾环境吗？许多数据科学家选择使用预先构建的机器学习库进行优化，但我们认为这种“即插即用”的学习方式会妨碍你的学习。因此，本课程将指导你从零开始构建一个优化算法。 在《人工智能：Python中的优化算法》课程中，你将学习优化算法背后的逻辑和数学。在两个实用的案例研究中，你也将了解到如何应用这些算法来解决现实世界的问题。 第一项案例研究中，我们将为六个朋友优化他们从同一机场出发的旅行计划。第二项案例研究将优化大学管理者为新生分配宿舍的方式。 在学习过程中，我们将了解什么是优化算法，如何将其应用于日常业务实践，并探索它们如何自主学习。本课程介绍四种类型的优化算法：随机搜索、爬山算法、模拟退火和遗传算法。即使你对这些术语还不熟悉，也不用担心，我们会逐一详细讲解，并在两个案例研究中展示如何构建这些算法。
What would an "optimal world" look like to you? Would people get along better? Would transport run faster? Would we take better care of our environment?Many data scientists choose to optimize by using pre-built machine learning libraries. But we think that this kind of 'plug-and-play' study hinders your learning. That's why this course gets you to build an optimization algorithm from the ground up.In Artificial Intelligence: Optimization Algorithms in Python, you'll get to learn all the logic and math behind optimization algorithms. With two highly practical case studies, you'll also find out how to apply them to solve real-world problems.In the first case study, we'll optimize travel plans for six friends who want to fly out from the same airport. In the second case study, we'll optimize the way university administrators allocate dorm rooms to new students.On the way, we'll learn what optimization algorithms are. We'll find out how they can be applied to daily business practice. And we'll see how they can learn by themselves. This course introduces you to four types of optimization algorithms: - random search - hill climb - simulated annealing, and - genetic Don't worry if you're not yet sure what any of these are. We'll go through each one in detail, and you'll find out how to build each of them in our two case studies."
