Introduction To Supervised Learning with R Programming | Skillshare

This class is all about the introduction to supervised learning with R programming.

Basic and intermediate R knowledge is required.

There are lots of free materials to learn about R, so please do take it before going to this class.

R studio is required to install before going to this class.

This class will assume you have a solid knowledge about R and I will not teach you R in this class.

This class is a beginner class for machine learning. You do not need to know any machine learning algorithm to take this class as I will explain to you in depth step-by-step.

Skills you will learn in this class:

Importing and Splitting the data.
Building your first machine learning model.
Eliminating missing data.
Compiling the model.
Standardizing the data.
Analysing and plotting data.
Evaluating the model’s performance.
Training the model.
By the end of this class, you will have a solid knowledge about the fundamental knowledge of supervised learning. You can use all these skills to build any other machine learning projects by using the structure in this class. All the codes will be explained carefully so you will have a deep understanding about all the steps in machine learning.

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