Regression, Data Mining, Text Mining, Forecasting using R
Duration: 32h57m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 4.9 GB
Genre: eLearning | Language: English
Duration: 32h57m | .MP4 1280x720, 30 fps(r) | AAC, 44100 Hz, 2ch | 4.9 GB
Genre: eLearning | Language: English
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
Requirements
Download R & RStudio before starting this tutorial
Download datasets folder in zipfile which is uploaded in starting of all sections
Description
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
Who this course is for:
All the IT professionals, whose experience ranges from '0' onwards are eligible to take this session. Especially professionals from data analysis, data warehouse, data mining, business intelligence, reporting, data science, etc, will naturally fit in well to take this course.
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