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DATA COLLECTION HARVESTING

IS IT A GLASS OF WINE OR A GLASS OF
BEER?

The data will be obtained by observing the visual
appearance of beer and wine (in this case, mugs/
glasses). Data could be collected on a variety of drink
elements,including everythingfrom the amount of foam
to the shape of the glass itself.

For the purposes of this explanation,we will concentrate
on just two of these factors: color (expressed as a
wavelengthoflight)andalcohol content(asapercentage).
It is expected that we will be able to divide our two drink
categories solely on these two characteristics. Colorand
alcohol will be referred to as “features” from now on.

DATA COLLECTION

Data collection, the first serious phase of machine
learning, is now underway. This stage is critical
because the accuracy of the predictive model is directly
proportional to the quality and quantity of data obtained.
In other words, the accuracy of the predictive model
will be directly determined by the data collected. In this
scenario,the data we collect will include the color of each
drink as well as the percentageof alcohol it contains.

Color Percentageof Label
(let’s sayinhex alcohol (wineorbeer)
code)
610 5 Beer

599 13 Wine
693 14 Wine
Figure 1
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