Welcome to Practical R Programming

Less Theory More Practice

Join the community for practical R insights and learning opportunities.

Welcome to Practical R

A computer screen displaying a coding interface with Python code related to machine learning. The code imports libraries like sklearn and deals with model metrics such as precision and recall. A classification report is shown along with a section titled 'Different meta model trained' listing various models like DT, RF, LR, and XGB. Below, there is code for tuning an XGB model using GridSearchCV.
A computer screen displaying a coding interface with Python code related to machine learning. The code imports libraries like sklearn and deals with model metrics such as precision and recall. A classification report is shown along with a section titled 'Different meta model trained' listing various models like DT, RF, LR, and XGB. Below, there is code for tuning an XGB model using GridSearchCV.
A textbook is open to Chapter 6, titled 'Regression Models for Overdispersed Count Response.' The page discusses various statistical models, including the negative binomial regression model, providing mathematical explanations and theoretical backgrounds.
A textbook is open to Chapter 6, titled 'Regression Models for Overdispersed Count Response.' The page discusses various statistical models, including the negative binomial regression model, providing mathematical explanations and theoretical backgrounds.

R Programming Insights

Practical R programming insights and advice tailored for all experience levels

Where to find practice datasets
Lines of computer code are displayed on a dark background, featuring SQL and JavaScript syntax with colorful syntax highlighting. The code includes a SQL query and JavaScript function handling datasets.
Lines of computer code are displayed on a dark background, featuring SQL and JavaScript syntax with colorful syntax highlighting. The code includes a SQL query and JavaScript function handling datasets.

Get some data and practice your skills

A computer screen displaying analytics dashboards with various charts, including a line graph on the left and a cohort analysis table on the right. The table is populated with different shades of blue, indicating varying levels of user activity over several weeks. Text labels and numbers detail user retention statistics.
A computer screen displaying analytics dashboards with various charts, including a line graph on the left and a cohort analysis table on the right. The table is populated with different shades of blue, indicating varying levels of user activity over several weeks. Text labels and numbers detail user retention statistics.
A computer screen displaying a code editor with a C++ program. The code includes a main function and nested for loops for printing stars. There are various sections of the interface visible, including a text editor with syntax highlighting, output panel showing build results, and project explorer on the side.
A computer screen displaying a code editor with a C++ program. The code includes a main function and nested for loops for printing stars. There are various sections of the interface visible, including a text editor with syntax highlighting, output panel showing build results, and project explorer on the side.
Fit for risk

Walkthrough of fitting the exponential distribution to a loss dataset

Key elements of practical time series analysis to get you started

Time series beginnings
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Get in Touch

Reach out for inquiries about R programming learning opportunities.

A laptop displaying coding software is placed on a wooden desk in a lecture hall. Behind the laptop, chalkboards can be seen with written equations and notes. The environment suggests an educational or programming context.
A laptop displaying coding software is placed on a wooden desk in a lecture hall. Behind the laptop, chalkboards can be seen with written equations and notes. The environment suggests an educational or programming context.
Practical R

Less theory more practice

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