Praktyczne szkolenia na żywo z Reinforcement Learning. Reinforcement Learning, czyli uczenie przez wzmacnianie jest dziedziną uczenia maszynowego. Ma miejsce, gdy komputer wykonuje zadanie metodą prób i błędów w dynamicznym środowisku ucząc się poprawnej odpowiedzi. Kursy obejmują między innymi stworzenie środowiska, agenta i zdefiniowanie nagrody, a także uczenie nadzorowane, nienadzorowane i przez wzmacnianie. Produktem szkolenia ma być trenowanie agenta i wdrożenie rozwiązań.
Szkolenie Reinforcement Learning jest dostępne jako "szkolenie stacjonarne" lub "szkolenie online na żywo".
Szkolenie stacjonarne może odbywać się lokalnie w siedzibie klienta w Polsce lub w ośrodkach szkoleniowych NobleProg w Polsce. Zdalne szkolenie online odbywa się za pomocą interaktywnego, zdalnego pulpitu DaDesktop .
NobleProg -- Twój lokalny dostawca szkoleń.
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Plany szkoleń z technologii Reinforcement Learning
Nazwa kursu
Czas trwania
Opis
Nazwa kursu
Czas trwania
Opis
21 godzin
Opis
Reinforcement Learning (RL) is a machine learning technique in which a computer program (agent) learns to behave in an environment by performing the actions and receiving feedback on the results of the actions. For each good action, the agent receives positive feedback, and for each bad action, the agent receives negative feedback (penalty).
This instructor-led, live training (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.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
This instructor-led, live training (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.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
21 godzin
Opis
Reinforcement Learning (RL) is an area of AI (Artificial Intelligence) used to build autonomous systems (e.e., an "agent") that learn by interacting with their environment in order to solve a problems. RL has applications in areas such as robotics, gaming, consumer modeling, healthcare, supply chain management, and more.
This instructor-led, live training (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.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
This instructor-led, live training (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.
Format of the Course
- Interactive lecture and discussion.
- Lots of exercises and practice.
- Hands-on implementation in a live-lab environment.
Course Customization Options
- To request a customized training for this course, please contact us to arrange.
Nadchodzące szkolenia z technologii Reinforcement Learning
2021-02-15 09:00:00
Katowice ul. Korfantego 2
21 godzin
2021-02-17 09:00:00
Katowice ul. Korfantego 2
21 godzin
2021-03-22 09:00:00
Warszawa, ul. Złota 3 / 11
21 godzin
2021-03-23 09:00:00
Warszawa, ul. Złota 3 / 11
21 godzin
Other regions
Other countries
Konsultacje
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