Vitrià i Marca, JordiBoldú Quirós, Josep2017-10-132017-10-132017-01-26https://hdl.handle.net/2445/116550Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2017, Director: Jordi Vitrià i MarcaThis project is based on a challenge provided by the website called Kaggle, which involves the creation of an automatic learning system that makes possible a prediction of clicks on online advertising. Assuming this challenge, a program that is able to predict ad clicks has been created, but by using new technologies like Docker, which makes possible a virtualization of a customized Linux environment ideal for programming Tensorflow, a library that enables an automatic, fast and flexible learning. The program’s main algorithm makes an automatic learning using a linear regression model that feeds from the database provided by Kaggle, which is destined for this challenge. This database is composed of a 10 day history of ad clicks and no clicks.36 p.application/pdfcatmemòria: cc-by-sa (c) Josep Boldú Quirós, 2017codi: GPL (c) Josep Boldú Quirós, 2017http://creativecommons.org/licenses/by-sa/3.0/eshttp://www.gnu.org/licenses/gpl-3.0.ca.htmlAprenentatge automàticAlgorismes computacionalsProgramariPublicitat per InternetMineria de dadesTreballs de fi de grauMachine learningComputer algorithmsComputer softwareInternet advertisingData miningBachelor's thesesinfo:eu-repo/semantics/bachelorThesisinfo:eu-repo/semantics/openAccess