Data Science Project on Wine Quality Prediction in R

Data Science Project on Wine Quality Prediction in R

In this R data science project, we will explore wine dataset to assess red wine quality. The objective of this data science project is to explore which chemical properties will influence the quality of red wines.
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SUBHABRATA BISWAS linkedin profile url

Lead Consultant, ITC Infotech

The project orientation is very much unique and it helps to understand the real time scenarios most of the industries are dealing with. And there is no limit, one can go through as many projects... Read More

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Camille St. Omer linkedin profile url

Artificial Intelligence Researcher, Quora 'Most Viewed Writer in 'Data Mining'

I came to the platform with no experience and now I am knowledgeable in Machine Learning with Python. No easy thing I must say, the sessions are challenging and go to the depths. I looked at graduate... Read More

What will you learn

Data Exploration
Asking the right questions for analysis
Data Visualisation
Storytelling
Applying regression models

Project Description

In this data science project, we will explore wine dataset for red wine quality. The objective is to explore which chemical properties influence the quality of red wines. As interesting relationships in the data are discovered, we’ll produce and refine plots to illustrate them.

We will learn how to ask the right questions for data analysis at certain points in the project. Finally, we would learn how to storyboard our analysis to create a final picture from our work to help decision makers understand how wine qualities were influenced.

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Curriculum For This Mini Project

Why we're using R and its benefits
04m
Introduction to Exploratory Data Analysis
02m
Exploring the key components of a dataset
02m
Data Munging
08m
Introducing the dataset and problem statement
07m
Univariate Plots Section
11m
Analysis of Plots
03m
Introduction to Boxplots
21m
Correlation and Bivariate Analysis
11m
Linear Model and Support Vector Machine Introductions
12m
Multivariate plot building and storyboarding
13m
Summarizing and beautifying the story
35m