Machine Learning with R
4.0 (1 rating)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
517 students enrolled

Machine Learning with R

Machine Learning and Statistical Learning with R
4.0 (1 rating)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
517 students enrolled
Created by SVBook Pte. Ltd.
Last updated 12/2018
English
Current price: $139.99 Original price: $199.99 Discount: 30% off
5 hours left at this price!
30-Day Money-Back Guarantee
This course includes
  • 2 hours on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • Machine Learning using R
Course content
Expand 30 lectures 01:48:33
+ Section
30 lectures 01:48:33
Getting Started 3
06:00
Read dataset
01:08
Some Explanations
04:04
Some Explanations 2
02:08
Simple Linear Regression
03:07
Build Linear Regression
00:43
Predict with Linear Regression
01:21
KMeans Clustering
03:05
KMeans Clustering in R
01:23
Agglomeration CLustering
03:45
Agglomeration CLustering in R
01:53
Decision Tree Algorithm: ID3
09:15
Decision Tree Algorithm: Split Train and Test set in R
02:51
Decision Tree ALgorithm: train ID3 tree
00:59
Decision Tree ALgorithm: predict ID3 tree
00:51
KNN Classification
03:50
KNN in R: train KNN
02:31
KNN in R: Predict
00:50
Naive Bayes ALgorithm
05:36
Naive Bayes in R
02:38
Neural Network
05:44
Neural Network in R
02:50
What Algorithm to Use?
01:35
Model Evaluation
03:44
Model Evaluation for Classification in R
04:18
Model Evaluation for Regression in R
01:59
Requirements
  • Fundamentals R programming
Description

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, and you can take a exam at EMHAcademy to get SVBook Certified Data Miner using R certificate : 

- 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)


Content

  1. Getting Started

  2. Getting Started 2

  3. Getting Started 3

  4. Data Mining Process

  5. Download Data set

  6. Read Data set

  7. Some Explanations

  8. Simple Linear Regression

  9. Build Linear Regression Models

  10. Predict Linear Regression Models

  11. KMeans Clustering

  12. KMeans Clustering in R

  13. Agglomeration Clustering

  14. Agglomeration Clustering in R

  15. Decision Tree ID3 ALgorithm

  16. Decision Tree in R: Split train and test set

  17. Decision Tree in R: Train Decision Tree

  18. Decision Tree in R: Predict Decision Tree

  19. KNN Classification

  20. Train KNN in R

  21. Predict KNN in R

  22. Naive Bayes Classification

  23. Naive Bayes in R

  24. Neural Network Classification

  25. Neural Network in R

  26. What Algorithm to Use?

  27. Model Evaluation

  28. Model Evaluation using R for Classification

  29. Model Evaluation using R for Regression

Who this course is for:
  • Beginner Data Scientist or Analyst interested in R programming