Logistic Regression, Decision Tree and Neural Network in R

Logistic Regression, Decision Tree and Neural Network in R, available at $19.99, has an average rating of 3.95, with 12 lectures, based on 32 reviews, and has 3000 subscribers.

You will learn about 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 This course is ideal for individuals who are Anyone seeking a career as data scientist, data analyst , finance analyst, statistician , actuary, just to name few It is particularly useful for Anyone seeking a career as data scientist, data analyst , finance analyst, statistician , actuary, just to name few.

Enroll now: Logistic Regression, Decision Tree and Neural Network in R

Summary

Title: Logistic Regression, Decision Tree and Neural Network in R

Price: $19.99

Average Rating: 3.95

Number of Lectures: 12

Number of Published Lectures: 12

Number of Curriculum Items: 12

Number of Published Curriculum Objects: 12

Original Price: $44.99

Quality Status: approved

Status: Live

What You Will 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

Who Should Attend

Anyone seeking a career as data scientist, data analyst , finance analyst, statistician , actuary, just to name few

Target Audiences

Anyone seeking a career as data scientist, data analyst , finance analyst, statistician , actuary, just to name few

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 Curriculum

Chapter 1: Introduction

Lecture 1: Introduction

Lecture 2: How to download R

Lecture 3: Welcome

Lecture 4: Description of the data

Lecture 5: Data transformation

Lecture 6: Missing values detection and treatment

Lecture 7: Data visualisation

Lecture 8: Training and Testing set

Lecture 9: Decision Tree

Lecture 10: Logistic regression

Lecture 11: Neural network

Lecture 12: Min Max normalization

Instructors

Modeste Atsague
Data Scientist, Statistician

Rating Distribution

1 stars: 3 votes
2 stars: 0 votes
3 stars: 6 votes
4 stars: 13 votes
5 stars: 10 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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