Applied Machine Learning With R
4.5 /5- Offered byEduonix
Applied Machine Learning With R at Eduonix Overview
Duration | 4 hours |
Mode of learning | Online |
Schedule type | Self paced |
Difficulty level | Intermediate |
Credential | Certificate |
Applied Machine Learning With R at Eduonix Highlights
- Learn about data science and how can you use it to strengthen your organization.
- Lifetime access to study material
- A great course for learning Machine Learning
- Self paced Course
Applied Machine Learning With R at Eduonix Course details
- Software developers and programmers, data scientists, data analysts, robotics professionals, and computation and educational professionals, among others.
- Create your own machine learning algorithms
- Learn machine learning and artificial intelligence the easiest way
- Applied Machine Learning with R is a hands-on course Machine Learning and Artificial Intelligence course. This course covers the core concepts of machine learning, along with machine learning algorithms. You will also learn how to implement those machine learning algorithms with R and after completion of the course, you will be able to use them in your own projects.
Applied Machine Learning With R at Eduonix Curriculum
Section 1 : Introduction
Introduction
Starting up- Machine learning with R
What is Artificial Intelligence and machine learning
Flow of machine learning
Machine Learning vs Deep Learning
Section 2 : R programming tool
R tool and installation
R data structures
Section 3 : H2O Package
Basics of Machine learning
Supervised and unsupervised learning
Case study- K means clustering
Installation of H2O package
Performing Regression with H2O
Analysing the regression with H2O
Section 4 : TensorFlow Package
Tensorflow package
Performing Regression with TensorFlow
Analysing the regression with TensorFlow
Performance of model using TensorFlow
Section 5 : First Machine Learning
Caret Package for Machine Learning
Machine Learning with dataset
Iris dataset Implementation
Evaluation of Algorithms with models
Selecting Best Model in Machine Learning
Section 6 : Artificial Neural Networks
Creating and Visualizing Neural networks
Demonstration of sample neural network
Prediction Analysis of neural network
Cross Validation Box plot
Activity- Dataset to Neural Network
Section 7 : Cluster Generation
Cluster Generation
Cluster Generation Output Analysis
Section 8 : Decision Trees
Decision Trees of Machine Learning
Car Evaluation Problem Statement
Plotting a Decision Tree
Prediction Analysis- Decision Tree
Section 9 : Text Mining
Introduction to Text Mining
Text Mining with R
Applied Machine Learning With R at Eduonix Entry Requirements
- Educational Qualifications
- Work Experience: You must have a basic knowledge of R.
- Not mentioned
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