
Corsi di formazione su Reinforcement Learning condotti da un formatore locale in diretta a Italia.
Recensioni
Mi piacciono gli esempi da spiegare
AUO友达光电(苏州)有限公司
Corso: OptaPlanner in Practice
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informazioni
Amr Alaa - FAB banak Egypt
Corso: Introduction to Data Science and AI (using Python)
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Imparare la nuova lingua.
FAB banak Egypt
Corso: Introduction to Data Science and AI (using Python)
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Timing di conoscenza di presentazione di sogge
Aly Saleh - FAB banak Egypt
Corso: Introduction to Data Science and AI (using Python)
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Utile e buono ascoltatore .. Interactive
Ahmed El Kholy - FAB banak Egypt
Corso: Introduction to Data Science and AI (using Python)
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Ahmed era molto interattivo e non mi ha pensato di rispondere a qualsiasi tipo di presentazione ben presentazione e flusso liscio del corso
Mohamed Ghowaiba - FAB banak Egypt
Corso: Introduction to Data Science and AI (using Python)
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Il corso è molto interessante essere il principale memosa da oggi
mohamed taher - FAB banak Egypt
Corso: Introduction to Data Science and AI (using Python)
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Le discussioni per ampliare i nostri orizzonti
FAB banak Egypt
Corso: Introduction to Data Science and AI (using Python)
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Schema generale del corso Reinforcement Learning
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:
- 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.