日本ライブ強化学習トレーニングコース。
お客様の声
私は説明するための例が好きです
AUO友达光电（苏州）有限公司
コース: OptaPlanner in Practice
Machine Translated
情報
Amr Alaa - FAB banak Egypt
コース: Introduction to Data Science and AI (using Python)
Machine Translated
新しい言語を学ぶ。
FAB banak Egypt
コース: Introduction to Data Science and AI (using Python)
Machine Translated
科目プレゼンテーション知識タイ
Aly Saleh - FAB banak Egypt
コース: Introduction to Data Science and AI (using Python)
Machine Translated
役に立つのと良いリスナー..インタラクティブ
Ahmed El Kholy - FAB banak Egypt
コース: Introduction to Data Science and AI (using Python)
Machine Translated
Ahmedは非常にインタラクティブであり、あらゆる種類の質問に答えても、コースの喜びと滑らかな流れに答えなかった
Mohamed Ghowaiba - FAB banak Egypt
コース: Introduction to Data Science and AI (using Python)
Machine Translated
コースは今や白い焦点が初めてのものです
mohamed taher - FAB banak Egypt
コース: Introduction to Data Science and AI (using Python)
Machine Translated
視野を広げるための議論
FAB banak Egypt
コース: Introduction to Data Science and AI (using Python)
Machine Translated
強化学習コース概要
コース名
期間
概要
コース名
期間
概要
21 時間
This instructor-led, live training in 日本 (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 時間
This instructor-led, live training in 日本 (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 時間
This instructor-led, live training in 日本 (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.
Last Updated:
今後の強化学習コース
Fundamentals of Reinforcement Learning
02-03-2022 10:00
21 時間
Fundamentals of Reinforcement Learning
02-03-2022 10:00
21 時間
Reinforcement Learning with Java
02-03-2022 10:00
21 時間
OpenAI Gym
17-03-2022 10:00
7 時間
OpenAI Gym
17-03-2022 10:00
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週末強化学習コース, 夜の強化学習トレーニング, 強化学習ブートキャンプ, 強化学習 インストラクターよる, 週末強化学習トレーニング, 夜の強化学習コース, 強化学習指導, 強化学習インストラクター, 強化学習レーナー, 強化学習レーナーコース, 強化学習クラス, 強化学習オンサイト, 強化学習プライベートコース, 強化学習1対1のトレーニング
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