National Repository of Grey Literature 92 records found  1 - 10nextend  jump to record: Search took 0.00 seconds. 
Predictive Modelling with Python
Duda, Jan ; Burgetová, Ivana (referee) ; Zendulka, Jaroslav (advisor)
The main goal of this bachelor thesis is get to know with the data mining and its domain, also with the Knowledge discovery in databases process. It shows the most importnant approaches, which are implemented in Python language afterwards. The case study contains the prediction of index S&P 500 describing stock market developments on the US stock exchange. Both classification and regression models are used for the forecasting. Model evaluation is reached by the Monte Carlo experimental method.
Homegrown Product Offering System
Doubek, Daniel ; Zendulka, Jaroslav (referee) ; Burget, Radek (advisor)
This thesis focuses on the design, implementation and testing of the information system which will be used to sell homemade products. It is intended primarily for smallholders and backyard keepers who are creating surpluses and would like to offer them. I focused especially on user-friendly design, but also on the system features and capabilities that make it easier to offer and sell these products. This system is implemented in PHP, framework Nette combined with MySQL, HTML with Bootstrap library and in JavaScript's library JQuery. As a part of this thesis I have created a user-friendly information system which meets the demands of users.
Comparison of Classification Methods
Dočekal, Martin ; Zendulka, Jaroslav (referee) ; Burgetová, Ivana (advisor)
This thesis deals with a comparison of classification methods. At first, these classification methods based on machine learning are described, then a classifier comparison system is designed and implemented. This thesis also describes some classification tasks and datasets on which the designed system will be tested. The evaluation of classification tasks is done according to standard metrics. In this thesis is presented design and implementation of a classifier that is based on the principle of evolutionary algorithms.
Analysis of Classification Methods
Juríček, Jakub ; Zendulka, Jaroslav (referee) ; Burgetová, Ivana (advisor)
This work deals with the classification methods used in the knowledge discovery from data process and discusses the possibilities of their validation and comparison. Through experiments, the work focuses on the analysis of four selected methods: Naive Bayes classificator, decision tree, neural network and SVM. Factors influencing basic characteristics such as training speed, classification speed, accuracy are examined. A part of the thesis is a desktop application, which is a tool for training, testing and validation of individual methods. Eleven reference data sets are selected for experimental purposes. At the end of this work experimental results of comparison and observed characteristics of classification methods are summarized.
Extension of User Profiles for Targeted Advertising Purposes
Hadač, Filip ; Burgetová, Ivana (referee) ; Zendulka, Jaroslav (advisor)
This thesis is devoted to designation and realisation of the extension of user profiles for improvement targeted advertising purposes. Web scraping is used for acquirement of new data information. Extracted data comes from two servers, ČSFD and Recepty. Data from ČSFD are film genres. Data from Recepty are categories of recepies. Streaming applications are used for processing of data and saving them to databases of user profiles. Preprocessing and machine learning classification algorithms are used for benefit evaluation of new informations for profiles in advertising campaigns. Evaluation of experiments shows that new informations have slight benefit in improvement advertising campaigns.
Application for Text Summarization
Mička, Jakub ; Zendulka, Jaroslav (referee) ; Bartík, Vladimír (advisor)
This work is focused on an implementation a web application, which is a tool for automatic English text summarization. In result, automatic text summarization is made by TextRank and Latent semantic analysis method. Both of these methods are improved by named entity recognition. The main benefit of this work is proving that using the named entity recognition with Latent semantic analysis and especially with TextRank method leads to creation of higher quality summaries. This quality of the summaries was verified by ROUGE metrics.
Scala Programming Language and Its Use for Data Analysis
Kohout, Tomáš ; Bartík, Vladimír (referee) ; Zendulka, Jaroslav (advisor)
This thesis deals with comparing the Scala programming language with other commonly used languages for data analysis. These languages are evaluated on the basis of the following categories: data manipulation and visualization, machine learning and concurent processing capabilities. The evaluation then shows the strengths and weaknesses of Scala. The strengths will be demonstrated on application for email categorization.
Relationship between Changes in Betting Odds and Results of Football Matches
Jurkovič, Juraj ; Bartík, Vladimír (referee) ; Zendulka, Jaroslav (advisor)
The goal of this thesis is to demonstrate techniques for solving web scraping and knowledge discovery tasks. The case study is focused on the extraction of data from bookmaker websites and subsequent analysis of collected data. The thesis demonstrates the implementation of web scraping task in Python language. The thesis describes selected implementation details for developing such a system and proposes a database schema that can be used for this purpose. Collected data is analyzed using statistical methods and frequent patterns are discovered in odds movements using apriori algorithm. Discovered relationships and frequent patterns are presented to the end user.
Vulnerability Detection Service of Web Page Libraries
Bednář, Radek ; Zendulka, Jaroslav (referee) ; Volf, Tomáš (advisor)
This thesis deals with the creating of an application for the detection of technologies used on websites and finding their vulnerabilities. Application is implemented using the Symfony Framework and the React.js library. The information source is the NVD database joined by data from the GitHub service. Apart from the detection of technologies, the application allows the user to manually create his own sets of technologies and share them using the URL address.
Information System of a Floorball Team
Zmek, Jakub ; Bartík, Vladimír (referee) ; Zendulka, Jaroslav (advisor)
This bachelor thesis is focused on study of web technologies and the subsequent creation of an information system for floorball team FbC Reative Aligators E for well-aranged statistics and event attendance management. The information systém is programmed as a web aplication with Nette framework support. The system allows logging to events (trainings, matches) and displaying off attendance. The systém automatically extracts data (matches, competition table, player statistics) from Czech floorbal websites and stores them in the database. The downloaded statistics are the publicly avaible in the informaction system.

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