Local instructor-led live Reinforcement Learning training courses in Magyarország.
Vélemények
Szeretem a példákat magyarázni
AUO友达光电（苏州）有限公司
Kurzus: OptaPlanner in Practice
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információ
Amr Alaa - FAB banak Egypt
Kurzus: Introduction to Data Science and AI (using Python)
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Új nyelv tanulása.
FAB banak Egypt
Kurzus: Introduction to Data Science and AI (using Python)
Machine Translated
Tárgyak bemutatása Tudás időzítése
Aly Saleh - FAB banak Egypt
Kurzus: Introduction to Data Science and AI (using Python)
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Hasznos és jó hallgató .. Interaktív
Ahmed El Kholy - FAB banak Egypt
Kurzus: Introduction to Data Science and AI (using Python)
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Ahmed nagyon interaktív volt, és nem bánta, hogy bármilyen kérdésre válaszoljon a jól megszerzésére és a sima áramlására
Mohamed Ghowaiba - FAB banak Egypt
Kurzus: Introduction to Data Science and AI (using Python)
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A kurzus nagyon érdekes a fő fókusza
mohamed taher - FAB banak Egypt
Kurzus: Introduction to Data Science and AI (using Python)
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A horizontunk kiszélesítése érdekében folytatott megbeszélések
FAB banak Egypt
Kurzus: Introduction to Data Science and AI (using Python)
Machine Translated
Reinforcement Learning Course Outlines
Kurzusnév
Időtartalma
Összefoglaló
Kurzusnév
Időtartalma
Összefoglaló
21 hours
This instructor-led, live training in Magyarország (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 hours
This instructor-led, live training in Magyarország (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 hours
This instructor-led, live training in Magyarország (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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Upcoming Reinforcement Learning Courses
Fundamentals of Reinforcement Learning
15-02-2022 09:30
21 hours
Fundamentals of Reinforcement Learning
15-02-2022 09:30
21 hours
Reinforcement Learning with Java
21-02-2022 09:30
21 hours
OpenAI Gym
11-03-2022 09:30
7 hours
OpenAI Gym
11-03-2022 09:30
7 hours
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