Overview
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Learn Regression Techniques, Data Mining, Forecasting, Text Mining using R
What you'll learn:- 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 Linear Regression
- Learn about the K-Means clustering algorithm & how to use R to accomplish this
- Learn about the science behind text mining, word cloud & sentiment analysis & accomplish the same using R
Data Science using Ris designed to cover majority of the capabilities of Rfrom 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 Rfor buildingRegression models
- Learn about the K-Means clustering algorithm & how to use Rto 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
