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Improving Bots Playing Starcraft II Game in PySC2 Environment
Krušina, Jan ; Škoda, Petr (referee) ; Smrž, Pavel (advisor)
The aim of this thesis is to create an automated system for playing a real-time strategy game Starcraft II. Learning from replays via supervised learning and reinforcement learning techniques are used for improving bot's behavior. The proposed system should be capable of playing the whole game utilizing PySC2 framework for machine learning. Performance of the bot is evaluated against the built-in scripted AI in the game.
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Classification of eMail Communication
Piják, Marek ; Herout, Adam (referee) ; Szőke, Igor (advisor)
This diploma's thesis is based around creating a classifier, which will be able to recognize an email communication received by Topefekt.s.r.o on daily basis and assigning it into classification class. This project will implement some of the most commonly used classification methods including machine learning. Thesis will also include evaluation comparing all used methods.
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Application of Machine Learning Algorithms for Generation of Checking Circuits
Lelkes, Olivér ; Mičulka, Lukáš (referee) ; Kaštil, Jan (advisor)
This bachelor thesis deals with application of machine learning algorithms for generation of checking circuits. It contains detailed descriptions of the individual algorithms of machine learning which have been chosen to achieve this purpose. Except familiarization with it's theoretical properties there are also parts devoted to the specific utilization of the mentioned algorithms in the form of classifiers. Classifiers can work with different settings which influence the accuracy of the learning and the subsequent classification. The differences between the individual classifiers and their settings are illustrated in the experimental part of the thesis. Experiments were conducted on various circuits, including the control units of the robot, developed on the Department of Computer Systems, Faculty of Information Technology, Brno University of Technology.
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Utilization of artificial intelligence in technical diagnostics
Konečný, Antonín ; Huzlík, Rostislav (referee) ; Zuth, Daniel (advisor)
The diploma thesis is focused on the use of artificial intelligence methods for evaluating the fault condition of machinery. The evaluated data are from a vibrodiagnostic model for simulation of static and dynamic unbalances. The machine learning methods are applied, specifically supervised learning. The thesis describes the Spyder software environment, its alternatives, and the Python programming language, in which the scripts are written. It contains an overview with a description of the libraries (Scikit-learn, SciPy, Pandas ...) and methods — K-Nearest Neighbors (KNN), Support Vector Machines (SVM), Decision Trees (DT) and Random Forests Classifiers (RF). The results of the classification are visualized in the confusion matrix for each method. The appendix includes written scripts for feature engineering, hyperparameter tuning, evaluation of learning success and classification with visualization of the result.
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Data Mining Case Study in Python
Stoika, Anastasiia ; Burgetová, Ivana (referee) ; Zendulka, Jaroslav (advisor)
This thesis focuses on basic concepts and techniques of the process known as knowledge discovery from data. The goal is to demonstrate available resources in Python, which enable to perform the steps of this process. The thesis addresses several methods and techniques focused on detection of unusual observations, based on clustering and classification. It discusses data mining task for data with the limited amount of inspection resources. This inspection activity should be used to detect unusual transactions of sales of some company that may indicate fraud attempts by some of its salespeople.
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Classification of heart beats using artificial neuronal networks
Doležalová, Radka ; Vítek, Martin (referee) ; Ronzhina, Marina (advisor)
This work deals with using of artificial neural networks (ANN) for ECG classification. The issue of ECG and ANN technique are described theoretically at first, the next section describes use of Matlab to design ANN and graphical user interface. ECG data (namely QRST segments from the orthogonal X- lead from seven phases of the experiment) obtained from experiments in isolated hearts of rabbits are used for learning and testing of the classifier. The result of this work is the software with GUI that allows user to set various parameters and structure of ANN. After learning phase, ANN realized in this work able to classify cardiac cycles according to their morphology into seven groups.
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Instance based learning
Martikán, Miroslav ; Polách, Petr (referee) ; Honzík, Petr (advisor)
This thesis is specialized in instance based learning algorithms. Main goal is to create an application for educational purposes. There are instance based learning algorithms (IBL), nearest neighbor algorithms and kd-trees described theoretically in this thesis. Practical part is about making of tutorial application. Application can generate data, classified them with nearest neighbor algorithm and is able of IB1, IB2 and IB3 algorithm testing.
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Application of Machine Learning Algorithms for the Generation of Checking Circuits
Lelkes, Olivér ; Krčma, Martin (referee) ; Kaštil, Jan (advisor)
Tato diplomová práce se zabývá využitím algoritmů strojového učení pro konstrukci hlídacích obvodů. Práce obsahuje popis principů hlídacích obvodů, jejich existující implementace a ostatní teoretické znalosti vztahující se k systémům odolným proti poruchám. Práce je zaměřena na aplikaci hlídacích obvodů na hardware komponentech se sekvenční logikou. Algoritmy strojového učení jsou trénovány pomocí datových množin, které se skládají ze vstup-výstup sekvencí hardwarových komponentů a ukládají se jako časové řady. Cílem práce je určení vhodnosti jednotlivých algoritmů pro jejich aplikaci v hlídacích obvodech. Pro dosažení tohoto cíle, bylo provedeno srovnání vybraných algoritmů strojového učení. Součástí práce je popis parametrů algoritmů a generování datových sad. Práce taktéž zahrnuje experimenty provedeny na dolnopropustném FIR filtru a jejich vyhodnocení. Podle výsledků experimentů je diskutováno, které algoritmy jsou použitelné v hlídacích obvodech.
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Intelligent Manager of Fantasy Premier League Game
Vasilišin, Maroš ; Burgetová, Ivana (referee) ; Hynek, Jiří (advisor)
Hra Fantasy Premier League poskytuje miliónom hráčov po celom svete možnosť stať sa na chvíľu manažérom svojho vlastného klubu. Výsledky a bodové ohodnotenie v hre závisia na správnom predvídaní, ako sa budú hráči chovať v skutočných futbalových zápasoch. Ak by pri tomto rozhodovaní pomáhal software na predikciu a analýzu budúcich výkonov hráčov, výsledky v hre sa môžu rapídne zlepšiť. Táto diplomová práca sa zaoberá návrhom a implementáciou predikčného modelu, ktorý využíva neurónové siete na predikcie časových radov počas celej sezóny v hre. Boli použité metódy na spracovanie dát o hráčoch a kluboch za posledné 4 sezóny. Výkonnosť a presnosť predikčných metód boli testované na dátach z poslednej sezóny Premier League a predikcie algoritmu sa vo väčšine prípadov blížili realite. Ak by sa užívateľ držal predikčného modelu v hre stopercentne, získal by väčší počet bodov ako bežný hráč, ktorý žiadny predikčný model nepoužíva.
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Online System for Visual Geo-Localization in Natural Environment
Pospíšil, Miroslav ; Čadík, Martin (referee) ; Brejcha, Jan (advisor)
The goal of this master thesis is creation of an online system serving as a performing application for presentation results of visual geo-localization in nature and mountain environment. The system offers the users to choose one of the pre-defined photographs or~to~upload one's own photography while choosing a file or inserting an URL address. The~system will localizate a camera of a given image based on a visual geo-localization. The~geo-localization uses the mountain horizon as a key characteristic when searching for similar horizons. The~curve line of the horizon is extracted by a fully automatic algorithm based on supervised learning and dynamic programming. Visual geo-localization running on the server which using new inversed index with cache politic. This allows further scaling of the system. The server processing detected horizon curve and respond with set of the best candidates on results. Results are visualised to the user in form of classic map, detailed sattelite view and rendering of found panorama.
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