
在線或現場、由講師指導的實時強化學習培訓課程通過交互式實踐演示如何創建和部署強化學習系統。強化學習培訓可作為“在線實時培訓”或“現場實時培訓”。在線實時培訓(又名“遠程實時培訓”)是通過交互式遠程桌面進行的。現場現場培訓可以在 台灣 中的客戶場所本地進行,也可以在 台灣 中的 NobleProg 公司培訓中心進行。 NobleProg——您當地的培訓提供商
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Testimonials
他給我們的例子。
JONATHAN MARIANO, si
Course: Artificial Intelligence (AI) for Managers
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實驗
JONATHAN MARIANO, si
Course: Artificial Intelligence (AI) for Managers
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介紹的練習和範例。
Marcos - JONATHAN MARIANO, si
Course: Artificial Intelligence (AI) for Managers
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機器勒寧的主題。
Víctor Edgar - JONATHAN MARIANO, si
Course: Artificial Intelligence (AI) for Managers
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老師的態度
Ivonne Guadalupe Avendaño Hernandez - JONATHAN MARIANO, si
Course: Artificial Intelligence (AI) for Managers
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所教授的概念清晰,實用,並且有助於瞭解如何使用AI和ML這個主題。
Miguel - JONATHAN MARIANO, si
Course: Artificial Intelligence (AI) for Managers
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講師的經驗和知識。
SERGIO BRAVO - JONATHAN MARIANO, si
Course: Artificial Intelligence (AI) for Managers
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也許是一些練習。
Hilario García - JONATHAN MARIANO, si
Course: Artificial Intelligence (AI) for Managers
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做法之一
JONATHAN MARIANO, si
Course: Artificial Intelligence (AI) for Managers
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教師學科的知識和處理
Zaira N. - JONATHAN MARIANO, si
Course: Artificial Intelligence (AI) for Managers
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創新,因為它是我們已經生活的東西。
jesus isaias - JONATHAN MARIANO, si
Course: Artificial Intelligence (AI) for Managers
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Reinforcement Learning課程大綱
- Understand the key concepts behind Deep Reinforcement Learning and be able to distinguish it from Machine Learning.
- Apply advanced Reinforcement Learning algorithms to solve real-world problems.
- Build a Deep Learning Agent.
- 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.
- 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.
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