Regression, Data Mining, Text Mining, Forecasting using R
- 3.8
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Brief Introduction
Learn Regression Techniques, Data Mining, Forecasting, Text Mining using RDescription
Data Science using R is designed to cover majority of the capabilities of R from Analytics & Data Science perspective, which includes the following:
- Learn about the basic statistics, including measures of central tendency, dispersion, skewness, kurtosis, graphical representation, probability, probability distribution, etc.
- Learn about scatter diagram, correlation coefficient, confidence interval, Z distribution & t distribution, which are all required for Linear Regression understanding
- Learn about the usage of R for building Regression models
- Learn about the K-Means clustering algorithm & how to use R to accomplish the same
- Learn about the science behind text mining, word cloud, sentiment analysis & accomplish the same using R
- Learn about Forecasting models including AR, MA, ES, ARMA, ARIMA, etc., and how to accomplish the same using R
- Learn about Logistic Regression & how to accomplish the same using R
Requirements
- Requirements
- Download R & RStudio before starting this tutorial
- Download datasets folder in zipfile which is uploaded in starting of all sections
ExcelR Solutions
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