Search results for: ARTIFICIAL INTELLIGENCE, MACHINE LEARNING, CNN, NEURAL NETWORKS, OPTIMIZATION ALGORITHMS - Bridge of Knowledge

Search

Search results for: ARTIFICIAL INTELLIGENCE, MACHINE LEARNING, CNN, NEURAL NETWORKS, OPTIMIZATION ALGORITHMS

Search results for: ARTIFICIAL INTELLIGENCE, MACHINE LEARNING, CNN, NEURAL NETWORKS, OPTIMIZATION ALGORITHMS

  • Deep Learning Basics 2023/24

    e-Learning Courses
    • K. Draszawka

    A course about the basics of deep learning intended for students of Computer Science. It includes an introduction to supervised machine learning, the architecture of basic artificial neural networks and their training algorithms, as well as more advanced architectures (convolutional networks, recurrent networks, transformers) and regularization and optimization techniques.

  • Deep neural networks for data analysis 24/25

    e-Learning Courses
    • J. Cychnerski
    • K. Draszawka

    This course covers introduction to supervised machine learning, construction of basic artificial deep neural networks (DNNs) and basic training algorithms, as well as the overview of popular DNNs architectures (convolutional networks, recurrent networks, transformers). The course introduces students to popular regularization techniques for deep models. Besides theory, large part of the course is the project in which students apply...

  • Artificial Intelligence

    e-Learning Courses
    • J. Dembski
    • M. Smiatacz

  • Artificial intelligence

    e-Learning Courses
    • J. Dembski
    • M. Smiatacz

  • Machine learning for PhD students

    e-Learning Courses
    • W. Artichowicz

    An introductory course in machine learning for PhD students from Department of Geotechnical and Hydraulic Engineering

  • L23_24 Artificial Intelligence in Healthcare

    e-Learning Courses
    • J. Rumiński

  • Deep neural networks for data analysis

    e-Learning Courses
    • K. Draszawka

    The aim of the course is to familiarize students with the methods of deep learning for advanced data analysis. Typical areas of application of these types of methods include: image classification, speech recognition and natural language understanding. Celem przedmiotu jest zapoznanie studentów z metodami głębokiego uczenia maszynowego na potrzeby zaawansowanej analizy danych. Do typowych obszarów zastosowań tego typu metod należą:...

  • Artificial Intelligence - Summer 2023/24

    e-Learning Courses
    • J. Dembski
    • A. Sobociński

  • Deep neural networks for data analysis 27/28

    e-Learning Courses
    • K. Draszawka

  • Deep neural networks for data analysis 25/26

    e-Learning Courses
    • K. Draszawka

  • Deep neural networks for data analysis 26/27

    e-Learning Courses
    • K. Draszawka

  • Systemy z Uczeniem Maszynowym / Systems with Machine Learning

    e-Learning Courses
    • J. Cychnerski

  • Systemy z Uczeniem Maszynowym / Systems with Machine Learning 2022/2023

    e-Learning Courses
    • J. Cychnerski

  • Computational Intelligence - 2023

    e-Learning Courses
    • Z. Kowalczuk
    • T. Białaszewski

    Widening the students knowledge about the selected methods of artificial intelligence

  • Computational Intelligence 2022

    e-Learning Courses
    • Z. Kowalczuk
    • T. Białaszewski
    • H. Kormański

    Widening the students knowledge about the selected methods of artificial intelligence

  • Computational Intelligence - sem. 2022/23

    e-Learning Courses
    • Z. Kowalczuk
    • T. Białaszewski

    Widening the students knowledge about the selected methods of artificial intelligence

  • Computational Intelligence - 2023/2024 sem.

    e-Learning Courses
    • Z. Kowalczuk
    • T. Białaszewski

    Widening the students knowledge about the selected methods of artificial intelligence

  • Computational Intelligence - sem. 2023/2024

    e-Learning Courses

    Widening the students knowledge about the selected methods of artificial intelligence

  • Team Strategies - sem. 2022/23

    e-Learning Courses
    • T. Białaszewski

    The main aim of the course is to familiarize students with the basic problems in team strategies, such as: the use of the particle swarm optimization algorithms, the ant colony optimization, stochastic distributed searches, algorithms for team strategy, multi-agent systems, modeling intelligent cooperation, simulations of social behavior. The form of passing the course is passing the exam and completing a project task

  • Team Strategies - sem. 2023/24

    e-Learning Courses
    • T. Białaszewski

    The main aim of the course is to familiarize students with the basic problems in team strategies, such as: the use of the particle swarm optimization algorithms, the ant colony optimization, stochastic distributed searches, algorithms for team strategy, multi-agent systems, modeling intelligent cooperation, simulations of social behavior. The form of passing the course is passing the exam and completing a project task

  • Team Strategies - sem. 2024/25

    e-Learning Courses
    • T. Białaszewski

    The main aim of the course is to familiarize students with the basic problems in team strategies, such as: the use of the particle swarm optimization algorithms, the ant colony optimization, stochastic distributed searches, algorithms for team strategy, multi-agent systems, modeling intelligent cooperation, simulations of social behavior. The form of passing the course is passing the exam and completing a project task

  • Podstawy uczenia maszynowego AI

    e-Learning Courses

    Podstawy uczenia maszynowego. Machine Learning fundamentals.

  • Algorytmy Optymalizacji Dyskretnej - ed. 2021/2022

    e-Learning Courses
    • K. Pastuszak

    In real-world applications, many important practical problems are NP-hard, therefore it is expedient to consider not only the optimal solutions of NP-hard optimization problems, but also the solutions which are “close” to them (near-optimal solutions). So, we can try to design an approximation algorithm that efficiently produces a near-optimal solution for the NP-hard problem. In many cases we can even design approximation algorithms...

  • Interactive Decision Making, Inżynieria Środowiska, Environmental Engineering, 2023/2024 (summer semester)

    e-Learning Courses
    • A. Jakubczyk-Gałczyńska
    • A. Siemaszko

    The course is designed for students of MSc Studies in Environmental Engineering (studies in Polish and English) Person responsible for the subject, carrying out lectures and tutorials: mgr inż. Agata.Siemaszko; agata.siemaszko@pg.edu.pl The person conducting the lectures and tutorials: dr inż. Anna Jakubczyk-Gałczyńska; anna.jakubczyk@pg.edu.pl The course is conducted using the Project-Based Learning (PBL) method. It provides...

  • Architectural project V Design for all

    e-Learning Courses
    • J. Cudzik
    • D. Sędzicki
    • M. Gawdzik

    This course centers on designing a modern hotel/student dormitory incorporating additional ground-floor services, such as restaurants, shops, and conference spaces. Students will tackle the challenge of creating a dynamic and flexible design responsive to the urban context and sustainability goals while using advanced conceptual tools such as artificial intelligence.This course aims to guide students in designing a hotel that serves...

  • [Soft Skills] Smart metering - social risk perception and risk governance (2023/2024)

    e-Learning Courses
    • S. Potrykus
    • M. Jaskólski
    • A. Augusiak

    The aim of the course is to broaden the understanding of the risks associated with technology and to present the concept of social risk perception and risk management in the context of smart metering technology. In the current phase of technological development - called the Fourth Industrial Revolution - rapid and profound changes are creating new, particularly destabilizing threats. In the increasingly complex technological systems...

  • Smart metering - social risk perception and risk governance (10h, 2 ECTS credits)

    e-Learning Courses
    • M. Galik
    • A. Klej

    The goal of the course is to broaden the understanding of technology-related risks and to present the concepts of social risk perception and risk governance in the context of smart metering technology. In current phase of technological development – known as the fourth industrial revolution – rapid and profound changes are setting up new and particularly destabilizing risks. In more and more complex technological systems that constitute...

  • Modeling the Networks - ed. 2021/2022

    e-Learning Courses

    The goal of this course is to present optimization problems for road networks, where the road network is a set of n distinct lines, or n distinct (open or closed) line segments, in the plane, such that their union is a connected region.

  • Oprogramowanie Systemów Elektronicznych 2023/2024

    e-Learning Courses
    • M. Kowalewski

    {mlang pl} Cel kursu: Programowanie urządzeń pomiarowych, obsługa interfejsów komputerowych, poznanie mechanizmów zwiększania wydajności oprogramowania (Win32 API, DLL, ODBC), projektowanie aplikacji wielozadaniowych. Dla studentów jakiego kierunku/stopnia studiów dany kurs jest przeznaczony: Przedmiot prowadzonych na studiach II stopnia.Obowiązkowy dla specjalności "Komputerowe Systemy Elektroniczne" i "Computer Electronic...

  • Oprogramowanie Systemów Elektronicznych 2021/2022

    e-Learning Courses
    • M. Kowalewski

    {mlang pl} Cel kursu: Programowanie urządzeń pomiarowych, obsługa interfejsów komputerowych, poznanie mechanizmów zwiększania wydajności oprogramowania (Win32 API, DLL, ODBC), projektowanie aplikacji wielozadaniowych. Dla studentów jakiego kierunku/stopnia studiów dany kurs jest przeznaczony: Przedmiot prowadzonych na studiach II stopnia.Obowiązkowy dla specjalności "Komputerowe Systemy Elektroniczne" i "Computer Electronic...

  • Infosystemy Elektroniczne 2023/2024

    e-Learning Courses
    • M. Kowalewski

    {mlang pl} Cel kursu: Poznanie zasad funkcjonowania różnorodnych infosystemów elektronicznych, obejmujących zastosowania przemysłowe i komercyjne elektroniki. Dla studentów jakiego kierunku/stopnia studiów dany kurs jest przeznaczony: Przedmiot prowadzonych na studiach II stopnia.Obowiązkowy dla specjalności "Komputerowe Systemy Elektroniczne" i "Computer Electronic Systems" na kierunku Elektronika.Obieralny dla specjalności...

  • Infosystemy Elektroniczne 2021/2022

    e-Learning Courses
    • M. Kowalewski

    {mlang pl} Cel kursu: Poznanie zasad funkcjonowania różnorodnych infosystemów elektronicznych, obejmujących zastosowania przemysłowe i komercyjne elektroniki. Dla studentów jakiego kierunku/stopnia studiów dany kurs jest przeznaczony: Przedmiot prowadzonych na studiach II stopnia.Obowiązkowy dla specjalności "Komputerowe Systemy Elektroniczne" i "Computer Electronic Systems" na kierunku Elektronika.Obieralny dla specjalności...

  • Computer controlled systems - 2022/2023

    e-Learning Courses
    • P. Raczyński

    materiały wspierające wykład na studiach II stopnia na kierunku ACR pod tytułem komputerowe systemy automatyki 1. Computer system – controlled plant interfacing technique; simple interfacing and with both side acknowledgement; ideas, algorithms, acknowledge passing. 2. Methods of acknowledgement passing: software checking and passing, using interrupt techniques, using readiness checking (ready – wait lines). The best solution...

  • CCS-lecture-2023-2024

    e-Learning Courses
    • P. Raczyński

    materiały wspierające wykład na studiach II stopnia na kierunku ACR pod tytułem komputerowe systemy automatyki 1. Computer system – controlled plant interfacing technique; simple interfacing and with both side acknowledgement; ideas, algorithms, acknowledge passing. 2. Methods of acknowledgement passing: software checking and passing, using interrupt techniques, using readiness checking (ready – wait lines). The best solution optimization...