Deterministic chaos is phenomenon from nonlinear dynamics and it belongs togreatest advances of twentieth-century science. Chaotic behavior appears apart ofmathematical equations also in wide range in observable nature, so as in there orig-inating time series. Chaos in time series resembles stochastic behavior, but apart ofrandomness it is totally deterministic and therefore chaotic data can provide us use-ful information. Therefore it is essential to have methods, which are able to detectchaos in time series, moreover to distinguish chaotic data from stochastic one. Herewe present and discuss the performance of standard and machine learning methodsfor chaos detection and its implementation on two well known simple chaotic dis-crete dynamical systems - Logistic map and Tent map, which fit to the most of thedefinitions of chaos.