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Course: Machine Learning with R

Machine Learning with R

  • Life Time Access
  • Certificate on Completion
  • Access on Android and iOS App
  • Self-Paced
About this Course

This is the bite size course to learn R Programming for Machine Learning and Statistical Learning. In CRISP DM data mining process, machine learning is at the modeling and evaluation stage. 

You will need to know some R programming, and you can learn R programming from my "Create Your Calculator: Learn R Programming Basics Fast" course. You will learn R Programming for machine learning and you will be able to train your own prediction models with naive bayes, decision tree, knn, neural network, linear regression, and evaluate your models very soon after learning the course.

You can take the course as follows, I may allow you to have the SVBook certificate in Data Mining using R in future after you passed a quiz and completed all the courses below: 

  • Create Your Calculator: Learn R Programming Basics Fast (R Basics)
  • Applied Statistics using R with Data Processing (Data Understanding and Data Preparation)
  • Advanced Data Visualizations using R with Data Processing (Data Understanding and Data Preparation, in future)
  • Machine Learning with R (Modeling and Evaluation)
Basic knowledge
  • Computer Knowledge
  • Basic coding knowledge
What you will learn

Content

  • Getting Started
  • Getting Started 2
  • Getting Started 3
  • Data Mining Process
  • Download Data set
  • Read Data set
  • Some Explanations
  • Simple Linear Regression
  • Build Linear Regression Models
  • Predict Linear Regression Models
  • KMeans Clustering
  • KMeans Clustering in R
  • Agglomeration Clustering
  • Agglomeration Clustering in R
  • Decision Tree ID3 ALgorithm
  • Decision Tree in R: Split train and test set
  • Decision Tree in R: Train Decision Tree
  • Decision Tree in R: Predict Decision Tree
  • KNN Classification
  • Train KNN in R
  • Predict KNN in R
  • Naive Bayes Classification
  • Naive Bayes in R
  • Neural Network Classification
  • Neural Network in R
  • What Algorithm to Use?
  • Model Evaluation
  • Model Evaluation using R for Classification
  • Model Evaluation using R for Regression
Curriculum
Number of Lectures: 30
Total Duration: 01:48:43
R
  • Getting Started  
  • Getting Started 2  
  • Getting Started 3  
  • Data Mining Process  
  • Download Data Set  
  • Read Data Set  
  • Some Explanations  
  • Some Explanations 2  
  • Simple Linear Regressions  
  • BUild Linear Regression Models  
  • Predict with Linear Regression Model  
  • KMeans Clustering  
  • Cluster using KMeans in R  
  • Agglomeration Clustering  
  • Agglomeration CLustering in R  
  • Decision Tree ID3 Algorithm  
  • Decision Tree in R Split Train and TEst Set  
  • Decision Tree in R Train Decision Tree  
  • Decision Tree in R Prediction with Decision Tree  
  • KNN CLassiifcation  
  • KNN in R Train KNN  
  • KNN in R Prediction  
  • Naive Bayes Classification  
  • Naive Bayes Classification in R  
  • NEural Network Classification  
  • NEural Network Classification in R  
  • What Algorithm to use?  
  • Model Evaluation  
  • MOdel EValuation for Classfication Model  
  • MOdel EValuation for Regression Model  
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