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Predicting wine prices using other features based on the kaggle data set

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AlexSananka/Wine-Price-Predection-Kaggle-Competetion

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Wine-Price-Predection-Kaggle-Competetion

This repository contains the solution for our group in the competition of predicting the price of a bottle of wine based on a collection of over one hundred thousand reviews and other product features.

The data description is given in kaggle like below:

File descriptions

train.csv - the training set

test.csv - the test set

Data Fields:

country (String): The country that the wine is from.

province (String): The province or state that the wine is from.

region_1 (String): The wine growing area in a province or state.

region_2 (String): Sometimes there are more specific regions within the wine growing area.

winery (String): The winery that made the wine.

variety (String): The type of grapes used to make the wine.]

designation (String): The vineyard within the winery where the grapes that made the wine are from.

taster_name (String): taster name.

taster_twitter_handle (String): taster twitter account name.

review (String): A few sentences from a sommelier describing the wine's taste, smell, look, feel, etc.

review_score (Numeric): Number of points WineEnthusiast rated the wine on a scale of 1-100.

TARGET: price (Numeric) The cost for a bottle of wine.

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