i) Imagine you are working as a Data Scientist for an Online Wine Shop named “The Wine Land”.
ii) As the name suggests, the online store specializes in selling different varieties of wines.
iii) The online store receives a decent amount of traffic and reviews from its users.
iv) Leverage the “reviews” data and draw actionable insights from it.
Build a predictive model for predicting the wine “variety”.
i) user_name - user_name of the reviewer.
ii) country -The country that the wine is from.
iii) review_title - The title of the wine review, which often contains the vintage.
iv) review_description - A verbose review of the wine.
v) designation - The vineyard within the winery where the grapes that made the wine are from.
vi) points - ratings given by the user. The ratings are between 0 -100.
vii) price - The cost for a bottle of the wine.
viii) province - The province or state that the wine is from.
ix) region_1 - The wine-growing area in a province or state (ie Napa).
x) region_2 - Sometimes there are more specific regions specified within a wine-growing area (ie Rutherford inside the Napa Valley), but this value can sometimes be blank.
xi) winery - The winery that made the wine.
xii) variety - The type of grapes used to make the wine,ie,dependent variable .