Značilnost okolja Kuberflow

diplomsko delo

Domen Krasnič (Author), Bojan Novak (Mentor)

Abstract

V današnjih modernih časih je vedno več podatkov, ki nam omogočajo lažje odločitve. Iz različnih podatkov pridobimo različne informacije in vzorce, pomembne za našo prihodnost. Zaradi vse večjih količin podatkov so se razvile številne rešitve za obravnavo le-teh. Ena izmed rešitev, ki se je razvila, je strojno učenje, ki ima sposobnost reševanja kompleksnih problemov z različnih področij. V diplomskem delu je predstavljeno Kubeflow okolje in tematika, tesno povezana z njim.

Keywords

Kubeflow okolje;strojno učenje;Kubernetes;diplomske naloge;

Data

Language:	Slovenian
Year of publishing:	2021
Typology:	2.11 - Undergraduate Thesis
Organization:	UM FERI - Faculty of Electrical Engineering and Computer Science
Publisher:	[D. Krasnič]
UDC:	004.85(043.2)
COBISS:	90233603
Views:	260
Downloads:	31
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	Kubeflow environment
Secondary abstract:	In these modern times, there is more and more data to help us make better decisions. Different data provide different information and patterns that are relevant for our future. The increasing volume of data has led to the development of a number of solutions to deal with it. One solution that has been developed is machine learning, which has the ability to solve complex problems in a variety of fields. The thesis presents the Kubeflow environment and the topics closely related to this environment.
Secondary keywords:	Kubeflow environment;machine learning;Kubernetes;
Type (COBISS):	Bachelor thesis/paper
Thesis comment:	Univ. v Mariboru, Fak. za elektrotehniko, računalništvo in informatiko, Informatika in tehnologije komuniciranja
Pages:	VI, 43 str.
ID:	13276908