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所在平台: Udemy |
课程主页: https://www.udemy.com/course/genetic-algorithms-in-python/
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课程名称:《Python中的遗传算法快速入门指南》 课程概述:准备提升您的职业技能,快速掌握遗传算法。您将能够将遗传算法应用到实际优化问题中,并能够在Python环境中快速实现它。该课程适合以下学习者:希望快速学习遗传算法以解决人工智能和机器学习问题,并希望掌握基于遗传算法的优化解决方案以及在Python中开发基于遗传算法的应用程序。 课程内容:约三小时的视频内容,包括: - 遗传算法简介及示例 - 完全用Python实现的遗传算法的四个应用案例 - 四个关于使用Python开发遗传算法应用的作业 课程结构:此课程设计为最大限度地减少学习时间,同时获得最大的学习成果,共分为十一部分: 1. 遗传算法流程图 2. 遗传算法的生物类比 3. 遗传算法的五个基本步骤 4. 遗传算法计算 - 迪奥方程 5. 遗传算法迪奥方程的Python实现 6. 遗传算法应用 - 消息生成(密码破解) 7. 遗传算法Python库 8. 遗传算法应用 - 背包问题 9. 遗传算法应用 - 八皇后问题 10. 遗传算法的问题与应用类型 11. 遗传算法小测验及相关问题 课程收益:注册此课程后,您将获得: - 终身访问课程内容的权限 - 理解遗传算法的五个步骤及其在人工智能和机器学习问题中的应用 - 掌握使用Python及其库实现遗传算法的基本技能 为什么选择此课程?每节课均设计为帮助学习者清晰理解遗传算法的每一个步骤,避免不必要的数学复杂性。课程通过逐步演示的方式展示了四个实际应用案例,并提供相应的练习,帮助学员巩固遗传算法在优化问题中的实际应用。注释的遗传算法小测验将帮助学习者复习所学材料。 课程成果: - 理解遗传算法与传统算法的区别 - 掌握遗传算法的五个基本步骤 - 学习如何使用Python及其库实现遗传算法 - 识别适合应用遗传算法的问题领域 为什么还要等呢?立即注册吧!爱因斯坦曾说:“一切必须尽可能简单,但不能简单得过头。”本课程旨在以简单而精确的方式介绍遗传算法,不涉及复杂的数学内容,确保感兴趣的学习者能够轻松实践给定的示例。每段课程视频都简短明了,聚焦单一主题,实用的遗传算法阶段从一开始就引入,课程中间适量覆盖必要的理论,以支持学习者从已知到未知的学习过程。 课程适合希望通过及时学习与教学获取必要知识的学习者。
Get ready to enhance your career profile with upgraded skill in Genetic AlgorithmGet ready to apply Genetic Algorithm to practical optimization problem quicklyGet ready to implement Genetic Algorithm in Python / Python Library quicklyENROLL FOR THE COURSE NOW IF:· You want to quickly Learn Genetic Algorithm to solve AI & ML problems.· You want to quickly master the GA based solutions to optimization problems.· You want to quickly develop GA based applications in Python.WHAT'S IN THE COURSE?· Approximately Three Hours of video content including· Quick Introduction to Genetic Algorithm with Examples· Four applications of Genetic Algorithm completely implemented in Python· Four assignments on developing application of Genetic Algorithm using Python.COURSE STRUCTURE:This course is designed such that it can be completed in minimal time with the maximum outcome. The course is divided into Eleven sections namely(i) GA Flow Diagram, (ii) GA Biological Analogy, (iii) GA Essential Five Phases,(iv) GA Calculations- Diophantine Equation, (v). GA Diophantine Equation - Python Implemented,(vi) GA Application- Message Generation (Password Cracking), (vii) GA Python Libraries,(viii) GA Application- Knapsack Problem, (ix) GA Application- Eight Queen Problem,(x) GA Issues and Application Types and (xi) GA Quiz with Issues before GA Practitioner.Each of these sections will help you learn and master the Genetic Algorithm with ease, providing you with the knowledge about various steps which are essential to successfully complete any optimization project.WHAT DO YOU GET AFTER YOU ENROLL FOR THIS COURSE?· Lifetime access to the content of this course· Grasp of the Five-Phases of Genetic Algorithm with application development to AI/ML problems.· Master the essential skills for implementation of Genetic Algorithm using Python and Python LibraryWHY TAKE THIS COURSE?Each of the lectures is designed such that the learner can get a clear understanding of all the steps in the genetic algorithm without involving unnecessary mathematical complexities. Four practical applications have been demonstrated step-by-step either hand-coded or by using Python / Python Library. The same problems are assigned as practice exercise to crystalize the practical implementation of Genetic Algorithm to optimization problems from the domain of AI. The Annotated GA Quiz Show shall help the learner to review the understanding of the material presented.OUTCOMES OF THE COURSE:UNDERSTAND the Genetic Algorithm viz-a-viz traditional conventional algorithms.KNOW the Essential Five Phases of the Genetic Algorithm.LEARN to implement the Genetic Algorithm using Python and Python Library.IDENTIFY the problem domains to apply the Genetic Algorithm.So why wait? Enroll Now!!!Albert Einstein said, "Everything must be made as simple as possible, but not simpler".This course aims at introducing the GA in simple and precise way without unnecessary mathematical complexity. It focuses mainly on bringing the genetic algorithm concepts home in simplest possible manner. The contents are explained in simplest possible manner such that anyone interested in learning the application of GA can practice the given examples without much ado. Each of the lecture videos is short, precise and focuses on single idea. The practical GA phases are introduced right at the beginning along with practice example. The minimum required theory is covered in the middle of the course. This course aims at introducing the learner to working of GA taking him/her from known-to-unknown. GA is evolutionary algorithm; the lesson plan of the GA module here has been designed to support evolutionary learning.Just-In-Time Learning with Just-In-Time Teaching of Just-What-Is-Required.What is GA: Evolutionary Optimizing AlgorithmWhy GA: Small, Simple and EffectiveHow GA: Five Simple PhasesWhen GA: Large Solution SpaceWhere GA: Artificial Intelligence and Machine Learning