Course Information
Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
1 Hour(s) 0 Minute(s)
Language
English
Taught by
Modeste Atsague
Rating
Course Overview
Logistic Regression, Decision Tree and Neural Network in R
In this course, we cover two analytics techniques: Descriptive statistics and Predictive analytics. For the predictive analytic, our main focus is the implementation of a logistic regression model a Decision tree and neural network. We well also see how to interpret our result, compute the prediction accuracy rate, then construct a confusion matrix .
By the end of this course , you will be able to effectively summarize your data , visualize your data , detect and eliminate missing values, predict futures outcomes using analytical techniques described above , construct a confusion matrix, import and export a data.
Course Content
- 1 section(s)
- 12 lecture(s)
- Section 1 Introduction
What You’ll Learn
- At the end of this Course, A student will be able to use Predictive analytics ( Decision tree , neural network or Logistic regression) to predict future outcomes. Some areas of application are the following: Actuarial Science, marketing, financial services, insurance, mobility, pharmaceuticals, healthcare, just to name a few
Skills covered in this course
Reviews
-
JJohn Cole
Short course and sweet.
-
AAlok Sharma
Match is good - but, the content leaves you wanting for more flavour
-
CColton Clark
Straight into explanation with minimal emphasis on required packages.
-
TTsafack mila louise
I strongly recommend this cocourse. Short and explicit video. cover the material listed in the timely manner
