Cursos de Reinforcement Learning impartidos por instructor en vivo en Colombia.
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AUO友达光电（苏州）有限公司
Curso: OptaPlanner in Practice
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Amr Alaa - FAB banak Egypt
Curso: Introduction to Data Science and AI (using Python)
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Aprender un nuevo idioma.
FAB banak Egypt
Curso: Introduction to Data Science and AI (using Python)
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Presentación del tema Temporizamiento del conoc
Aly Saleh - FAB banak Egypt
Curso: Introduction to Data Science and AI (using Python)
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servicial y buen oyecto. Interactivo
Ahmed El Kholy - FAB banak Egypt
Curso: Introduction to Data Science and AI (using Python)
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Ahmed fue muy interactivo y no le importó responder a cualquier tipo de preguntas bien presentación y flujo suave del curso
Mohamed Ghowaiba - FAB banak Egypt
Curso: Introduction to Data Science and AI (using Python)
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El curso es muy interesante ser el enfoque principal ahora Nowdays
mohamed taher - FAB banak Egypt
Curso: Introduction to Data Science and AI (using Python)
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FAB banak Egypt
Curso: Introduction to Data Science and AI (using Python)
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Programas de los cursos Reinforcement Learning
Nombre del Curso
Duración
Descripción General
Nombre del Curso
Duración
Descripción General
21 horas
This instructor-led, live training in Colombia (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 horas
This instructor-led, live training in Colombia (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 horas
This instructor-led, live training in Colombia (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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