Decision Trees Modeling Supervised Learning using R

Decision Trees Modeling & Supervised Learning using R, available at Free, has an average rating of 3.83, with 14 lectures, based on 3 reviews, and has 4050 subscribers.

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You will learn about This course includes learning decision tree modeling which are used by data scientists or people who aspire to be the data scientist Decision Tree Regression Decision Tree Theory Implementation of Decision Tree Classifications using R This course is ideal for individuals who are Anyone who wants to learn about data and analytics or Data Engineers, Analysts, Architects, Software Engineers, IT operations, Technical managers It is particularly useful for Anyone who wants to learn about data and analytics or Data Engineers, Analysts, Architects, Software Engineers, IT operations, Technical managers.

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Summary

Title: Decision Trees Modeling & Supervised Learning using R

Price: Free

Average Rating: 3.83

Number of Lectures: 14

Number of Published Lectures: 14

Number of Curriculum Items: 14

Number of Published Curriculum Objects: 14

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

This course includes learning decision tree modeling which are used by data scientists or people who aspire to be the data scientist

Decision Tree Regression

Decision Tree Theory

Implementation of Decision Tree Classifications using R

Who Should Attend

Anyone who wants to learn about data and analytics

Data Engineers, Analysts, Architects, Software Engineers, IT operations, Technical managers

Target Audiences

Anyone who wants to learn about data and analytics

Data Engineers, Analysts, Architects, Software Engineers, IT operations, Technical managers

The web is full of apps that are driven by data. All the e-commerce apps and websites are based on data in the complete sense. There is database behind a web front end and middleware that talks to a number of other databases and data services. But the mere use of data is not what comprises of data science. A data application gets its value from data and in the process creates value for itself. This means that data science enables the creation of products that are based on data. This course includes learning decision tree modeling which are used by data scientists or people who inspire to be the data scientist. The tutorials will include the following;

Decision Tree Theory

Implementation using R Decision Tree Classification

Decision Tree Regression

Decision Tree in R is a machine-learning algorithm that can be a classification or regression tree analysis. The decision tree can be represented by graphical representation as a tree with leaves and branches structure. The leaves are generally the data points and branches are the condition to make decisions for the class of data set. Decision trees in R are considered as supervised Machine learning models as possible outcomes of the decision points are well defined for the data set. It is also known as the CART model or Classification and Regression Trees. There is a popular R package known as rpart which is used to create the decision trees in R.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Introduction to Decision Trees

Lecture 2: Route Node

Lecture 3: Route Node Continue

Chapter 2: Advertisement Dataset

Lecture 1: Advertisement Dataset

Lecture 2: Data Preprocessing

Lecture 3: Feature Scaling

Lecture 4: Classifier – rpart

Lecture 5: Confusion Matrix

Chapter 3: Diabetes Dataset

Lecture 1: Diabetes Dataset

Lecture 2: Plot Model-Classifier

Lecture 3: Prediction

Chapter 4: Caeseats Dataset

Lecture 1: Caeseats Dataset

Lecture 2: Split

Lecture 3: Tree Package

Instructors

EDUCBA Bridging the Gap
Learn real world skills online

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