r programming

Random forest in R using the tidymodels framework

The Random forest algorithm is one of the most used algorithm for building machine learning models. The random forest algorithm is a tree based algorithm that combines several decision trees of varying depth, and it is mostly used for classification problems.

Kruskal-wallis test in r (Simple guide)

A simple guide to performing kruskal wallis test in R

Visualizing and interpreting correlation in R

R is a good statistical tool for performing so many statistical tests. In this lesson i will walk you through how to test/interpret correlation between varibles in r.

Text mining with R

Text mining gets easier everyday with advent of new methods and approach. In this lesson i will walk you through how you can use R/Rstudio with the combination of some powerful packages to make sense out of unstructured text data and even go further to build a predictive model.

Anova in r

Conducting one-way and two-way analysis of variance (ANOVA) test in R

Logistic regression in r

In this lesson we will try to understand Logistic Regression in r and how to build a predictive model with it.

Linear regression in r

Building a linear regression model in r using both the base r and the tidymodels approach

Data Cleaning and Analysis with the tidyverse r package

A detailed explanation on how the tidyverse r package can be used to perform data cleaning and analysis

Predicting the result of a Virtual football match using tidymodels

Predicting the result of a virtual football game with SVM and random forest algorithms using the tidymodels r package

web scraping using RSelenium in R/Rstudio

Scraping the content of a site with login requirement and iframe using the RSelenium r package can be very easy. In this lesson you will learn how.....