Data Science

when dealing with Data Science we are more interested in these two arguments

quality and factibility

When dealing with Big Data we aree dealing with processing

information

Statistical Entropy can be see is a measure of

order

In the scientific method, within the analysis, observation must be followed by

measurement

In python, we use previously developed packages such as

a) pandas b)numpy c)mathplotlib d) all of the above

all of the above

Big data in theory deals

information

Mark the order in which you would do this activities when doing classification

( ) selection of the model

( ) selection of the attribute to be used as class attribute

( ) data gathering

( ) data cleaning

1 - Data Gathering

2- Data cleaning

3 - Selection of the attribute to be used as class attribute

4- Selection of the model

According to Saint Thomas, truth can be seen as a

metric

In the application of Data Science we must always provide

reference where the experience was obtained

When using the scientific method truth is found

across the universe

The confusion matrix can be defined as

matrix used to find the kappa values

using base 2, entropy goes from 0 to

infinity

The Kappa values goes from -1 to 1 (T/F)

true

in python we use pandas

dataframes