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所在平台: Udemy |
课程主页: https://www.udemy.com/course/advanced-dynamic-programming/
课程评论：没有评论
**课程名称：** 高级动态规划 **课程概述：** 本课程旨在教授学员一套解决动态规划问题的有效方法论，尤其针对那些已经对动态规划有一定了解但仍觉得实施困难的学习者。课程不适合初学者。 **课程内容：** * **动态规划实现技巧：** 学习作者独创的、易于实现任何动态规划问题的实用方法。 * **挑战性练习：** 课程包含一系列由讲师自行设计的、难度较高的练习题，涵盖了多种领域，并包含真实世界问题的案例。 * **Python实现：** 所有解决方案均使用Python编写，因为Python在实现动态规划算法和处理数据结构（如列表、元组等）方面具有简洁易用的特点。学员也可选择其他常用编程语言。 * **核心概念：** * 寻找最小值/最大值 * 寻找最小化/最大化某一价值的最佳路径 * 发现最小化/最大化某一价值的子集 **学习建议：** * 鼓励学员花时间理解并解决每一个练习题，不必急于求成。 * 即使遇到困难的题目，也不要跳过，因为之后的题目可能更具挑战性。 **目标学员：** * 熟悉动态规划基础，并希望进一步提升解决复杂动态规划问题的能力。
Dynamic programming is by far a very useful technique, but sometimes it can be difficult to be implemented correctly.In this course I'm going to show you the methodology that I use, to solve easily any DP problem!You are going to deal with some hard-to-solve exercises. So this is not a course for beginners, but for those who are more familiar with dynamic programming.Take your time in every exercise, there is no reason to hurry up.You should know that all these exercises are created by myself. I tried to cover many fields (included cases from real-life problems).All solutions are implemented in Python. I think it's one of the easiest programming languages to implement DP algorithms and deal easily with data structures (1D-Lists, 2D-Lists, Tuples etc).Of course you can implement DP algorithms in any programming language of wide use.There is no reason to skip an exercise, if you think it's difficult enough for you. Probably the next one will be harder.The concepts that we will cover are:find the minimum / maximum valuefind the best path which minimizes / maximizes a valuediscover a subset that minimizes / maximizes a valueI hope you enjoy this course!
