Słupsk

Słupski Inkubator Technologiczny, Portowa 13b, Słupsk, Polska, 76-200
Sala szkoleniowa położona jest zaledwie 3 kilometry od centrum miasta. Jest to dogodna lokalizacja, która umożliwia łatw...

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Deep Reinforcement Learning with Python

21 godzin
Deep Reinforcement Learning refers to the ability of an "artificial agent" to learn by trial-and-error and rewards-and-punishments. An artificial agent aims to emulate a human's ability to obtain and construct knowledge on its own, directly from raw inputs such as vision. To realize reinforcement learning, deep learning and neural networks are used. Reinforcement learning is different from machine learning and does not rely on supervised and unsupervised learning approaches. This instructor-led, live training (online or onsite) is aimed at developers and data scientists who wish to learn the fundamentals of Deep Reinforcement Learning as they step through the creation of a Deep Learning Agent. By the end of this training, participants will be able to:
  • 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.
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.
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Fundamentals of Reinforcement Learning

21 godzin
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.
Więcej...

Reinforcement Learning with Java

21 godzin
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 problem. 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.
Więcej...

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Opinie uczestników (13)

Poziom szkolenia był na wysokim poziomie. Prowadzący nie bał się używać matematycznych formalizmów.

Mateusz Soczewka - Santander Bank Polska S.A.
Szkolenie - Fundamentals of Reinforcement Learning

Przykłady z życia oraz praktyczne podejście do tematu.

Damian Pierończyk - Tech-Com sp. z o.o.
Szkolenie - OptaPlanner in Practice

przykłady i ćwiczenia

Kamil
Szkolenie - Introduction to Data Science and AI using Python

Kontakt z prowadzącą - Anna była bardzo dobrą rozmówczynią i świetną prowadzącą - słuchała naszych pytań, opinii i przemyśleń i bardzo aktywnie odpowiadała na nasze potrzeby - czy to pokazując dodatkowe rzeczy, albo modyfikując przykłady tak, by odzwierciedlały w jakiś sposób problemy, z jakimi możemy się spotkać w naszej dziedzinie operacji.

Bartosz Kratochwil
Szkolenie - Introduction to Data Science and AI using Python

The training definitely backfilled some of the gaps in my knowledge left by reading the OptaPlanner userguide. It gave me a good broad understanding of how to approach using OptaPlanner in our projects going forward.

Terry Strachan - Exel Computer Systems plc
Szkolenie - OptaPlanner in Practice

The course is very interesting being the main focus nowdays

mohamed taher - FAB banak Egypt
Szkolenie - Introduction to Data Science and AI (using Python)

Ahmed was very interactive and didn’t mind answering any kind of questions Well presentation and smooth flow of the course

Mohamed Ghowaiba - FAB banak Egypt
Szkolenie - Introduction to Data Science and AI (using Python)

Helpful and good listener .. interactive

Ahmed El Kholy - FAB banak Egypt
Szkolenie - Introduction to Data Science and AI (using Python)

Wszystkie przedstawione informacje

Jose Victor - si
Szkolenie - Artificial Intelligence (AI) for Managers

Przetłumaczone przez sztuczną inteligencję

Podane ćwiczenia i przykłady.

Marcos - si
Szkolenie - Artificial Intelligence (AI) for Managers

Przetłumaczone przez sztuczną inteligencję

Tematy związane z Machine Lerning.

Víctor Edgar - si
Szkolenie - Artificial Intelligence (AI) for Managers

Przetłumaczone przez sztuczną inteligencję

Postawa nauczyciela

Ivonne Guadalupe Avendaño Hernandez - si
Szkolenie - Artificial Intelligence (AI) for Managers

Przetłumaczone przez sztuczną inteligencję

Nauczane koncepcje były jasne, praktyczne i bardzo pomocne w zrozumieniu, jak korzystać z tego tematu AI i ML.

Miguel - si
Szkolenie - Artificial Intelligence (AI) for Managers

Przetłumaczone przez sztuczną inteligencję

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Reinforcement Learning Konsultacje
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