在中国由讲师进行实时指导的Reinforcement Learning本地培训课程。
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我喜欢实例讲解
AUO友达光电（苏州）有限公司
课程: OptaPlanner in Practice
资讯
Amr Alaa - FAB banak Egypt
课程: Introduction to Data Science and AI (using Python)
Machine Translated
学习新语言
FAB banak Egypt
课程: Introduction to Data Science and AI (using Python)
Machine Translated
主题演示知识时序
Aly Saleh - FAB banak Egypt
课程: Introduction to Data Science and AI (using Python)
Machine Translated
有帮助和好听众..互动
Ahmed El Kholy - FAB banak Egypt
课程: Introduction to Data Science and AI (using Python)
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艾哈迈德是非常互动的，不介意回答任何类型的问题良好的演示和流畅的流程
Mohamed Ghowaiba - FAB banak Egypt
课程: Introduction to Data Science and AI (using Python)
Machine Translated
这个课程非常有趣的是主要焦点截止日期
mohamed taher - FAB banak Egypt
课程: Introduction to Data Science and AI (using Python)
Machine Translated
拓宽视野的讨论
FAB banak Egypt
课程: Introduction to Data Science and AI (using Python)
Machine Translated
Reinforcement Learning课程大纲
课程名称
课程时长
课程概览
课程名称
课程时长
课程概览
21小时
This instructor-led, live training in 中国 (online or onsite) is aimed at data scientists who wish to create and deploy a Reinforcement Learning system, capable of making decisions and solving real-world problems within an organization.
By the end of this training, participants will be able to:
- Understand the relationships and differences between Reinforcement Learning and machine learning, deep learning, supervised and unsupervised learning.
- Analyze a real-world problem and redefine it as Reinforcement Learning problem.
- Implementing a solution to a real-world problem using Reinforcement Learning.
- Understand the different algorithms available in Reinforcement Learning and select the most suitable one for the problem at hand.
By the end of this training, participants will be able to:
- Understand the relationships and differences between Reinforcement Learning and machine learning, deep learning, supervised and unsupervised learning.
- Analyze a real-world problem and redefine it as Reinforcement Learning problem.
- Implementing a solution to a real-world problem using Reinforcement Learning.
- Understand the different algorithms available in Reinforcement Learning and select the most suitable one for the problem at hand.
21小时
This instructor-led, live training in 中国 (online or onsite) is aimed at data scientists who wish to go beyond traditional machine learning approaches to teach a computer program to figure out things (solve problems) without the use of labeled data and big data sets.
By the end of this training, participants will be able to:
- Install and apply the libraries and programming language needed to implement Reinforcement Learning.
- Create a software agent that is capable of learning through feedback instead of through supervised learning.
- Program an agent to solve problems where decision making is sequential and finite.
- Apply knowledge to design software that can learn in a way similar to how humans learn.
By the end of this training, participants will be able to:
- Install and apply the libraries and programming language needed to implement Reinforcement Learning.
- Create a software agent that is capable of learning through feedback instead of through supervised learning.
- Program an agent to solve problems where decision making is sequential and finite.
- Apply knowledge to design software that can learn in a way similar to how humans learn.
7小时
This instructor-led, live training in 中国 (online or onsite) is aimed at researchers and developers who wish to install, configure, customize, and implement OpenAI Gym to quickly develop reinforcement learning algorithms.
By the end of this training, participants will be able to build, develop, execute, and test reinforcement learning algorithms to optimize tasks and achieve maximum results.
By the end of this training, participants will be able to build, develop, execute, and test reinforcement learning algorithms to optimize tasks and achieve maximum results.
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