- Your comprehensive guide to Regression Analysis & supervised machine learning using R-programming language
- Graphically representing data in R before and after analysis
- It covers the theory and applications of supervised machine learning with the focus on regression analysis using the R-programming language in R-Studio
- Implement Ordinary Least Square (or simple linear) regression, Random FOrest Regression, Decision Trees, Logistic regression and others using R
- Perform model’s variable selection and assess regression model’s accuracy
- Build machine learning based regression models and test their performance in R
- Compare different different machine learning models for regression tasks in R
- Learn how to select the best statistical & machine learning model for your task
- Learn when and how machine learning models should be applied
- Carry out coding exercises & your independent project assignment

- Availabiliy computer and internet & strong interest in the topic

My course will be your hands-on guide to the theory and applications of

Unlike other courses, it offers NOT ONLY the guided demonstrations of the R-scripts but also covers theoretical background that will allow you to FULLY UNDERSTAND & APPLY REGRESSION ANALYSIS (Linear Regression, Random Forest, KNN, etc) in R (many R packages incl. caret package will be covered) for supervised machine learning and prediction tasks.

This course also covers all the main aspects of practical and highly applied data science related to Machine Learning (i.e. regression analysis). Thus, if you take this course, you will save lots of time & money on other expensive materials in the R based Data Science and Machine Learning domain.

- Fully understand the basics of Regression Analysis (parametric & non-parametric methods) & supervised Machine Learning from theory to practice
- Harness applications of parametric and non-parametric regressions in R
- Learn how to apply correctly regression models and test them in R
- Learn how to select the best statistical & machine learning model for your task
- Carry out coding exercises & your independent project assignment
- Learn the basics of R-programming
- Get a copy of all scripts used in the course
- and MORE

You’ll start by absorbing the most valuable Regression Analysis & R-programming basics, and techniques. I use easy-to-understand, hands-on methods to simplify and address even the most difficult concepts in R.

My course will help you implement the methods using real data obtained from different sources. Thus, after completing my Regression Analysis for Machine Learning in R course, you’ll easily use different data streams and data science packages to work with real data in R.

In case it is your first encounter with R, don’t worry, my course a full introduction to the R & R-programming in this course.

The course is ideal for professionals who need to use cluster analysis, unsupervised machine learning, and R in their field.

- The course is ideal for professionals who need to use regression analysis & supervised machine learning in their field
- Everyone who would like to learn Data Science Applications In The R & R Studio Environment
- Everyone who would like to learn theory and implementation of Regression Analysis & Machine Learning On Real-World Data

Source: https://www.udemy.com/course/regression-analysis-in-machine-learning-statistics-in-r/

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