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ML-for-Object-Classification

Machine Learning For Whiskies Classification Using Flavours

OBJECT || Scotch Whisky

Scotch whisky is prized for its complexity and variety of flavors.And the regions of Scotland where it is produced are believed to have distinct flavor profiles.In this case study, we will classify scotch whiskies based on their flavor characteristics. The dataset we'll be using contains a selection of scotch whiskies from several distilleries, and we'll attempt to cluster whiskies into groups that are similar in flavor.

Dependencies : Pandas, NumPy, and scikit-learn, and perhaps of scotch whisky.

Dataset :: whiskies.txt,regions.txt

The dataset we'll be using consists of tasting ratings of one readily available single malt scotch whisky from almost every active whisky distillery in Scotland.The resulting dataset has 86 malt whiskies that are scored between 0 and 4 in 12 different taste categories.The scores have been aggregated from 10 different tasters.The taste categories describe whether the whiskies are sweet, smoky,medicinal, spicy, and so on.

The Repository consists of following modules ::::

-->> 1.Loding and inspecting whiskies data

-->> 2.Exploring Correlations  

-->> 3.Clustering Whiskies By Flavours

-->> 4.Whiskies Comparing Correlation

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