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Applied Machine Learning With R

Machine learning is changing the manner in which we use data and training system. It has gradually spread it's span through our gadgets, from self-driving cars to the computerized chatbots. To charact...

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Course Description

Machine learning is changing the manner in which we use data and training system. It has gradually spread it's span through our gadgets, from self-driving cars to the computerized chatbots. To characterize machine learning in the most straightforward terms, it is essentially the capacity to prepare computers to think for themselves in light of the situations that occurs. With machine learning n...

Machine learning is changing the manner in which we use data and training system. It has gradually spread it's span through our gadgets, from self-driving cars to the computerized chatbots. To characterize machine learning in the most straightforward terms, it is essentially the capacity to prepare computers to think for themselves in light of the situations that occurs. With machine learning now being part of all major businesses it is important for developers to get a hang of this amazing technology. Machine learning is a complex concept that uses algorithms to configure coding that will enable the computers to learn from lot of data. We have created a simple and easy course to help you learn ML and AI using R. Our course on Machine Learning with R helps you understand the core concepts of machine learning followed by different machine learning algorithms and implementing those machine learning algorithms with R. At the end of this practical and hands-on course, you will have all that you need to really begin using machine learning algorithms and you will learn to add them in your own projects.

What you’ll learn
  • Machine Learning concepts
  • Difference between Machine learning and Deep learning
  • R Tool (Installation and packages)
  • Tensorflow and H2O packages
  • Artificial Neural Networks
  • Decision trees and Text Mining

Covering Topics

1
Section 1 : Introduction
2
Section 2 : R programming tool
3
Section 3 : H2O Package
4
Section 4 : TensorFlow Package
5
Section 5 : First Machine Learning
6
Section 6 : Artificial Neural Networks
7
Section 7 : Cluster Generation
8
Section 8 : Decision Trees
9
Section 9 : Text Mining

Curriculum

      Section 1 : Introduction
1
Introduction Preview
2
Starting up- Machine learning with R
3
What is Artificial Intelligence and machine learning
4
Flow of machine learning Preview
5
Machine Learning vs Deep Learning
      Section 2 : R programming tool
6
R tool and installation
7
R data structures
      Section 3 : H2O Package
8
Basics of Machine learning
9
Supervised and unsupervised learning
10
Case study- K means clustering Preview
11
Installation of H2O package
12
Performing Regression with H2O
13
Analysing the regression with H2O
      Section 4 : TensorFlow Package
14
Tensorflow package
15
Performing Regression with TensorFlow
16
Analysing the regression with TensorFlow
17
Performance of model using TensorFlow
      Section 5 : First Machine Learning
18
Caret Package for Machine Learning
19
Machine Learning with dataset
20
Iris dataset Implementation
21
Evaluation of Algorithms with models
22
Selecting Best Model in Machine Learning
      Section 6 : Artificial Neural Networks
23
Creating and Visualizing Neural networks
24
Demonstration of sample neural network
25
Prediction Analysis of neural network
26
Cross Validation Box plot
27
Activity- Dataset to Neural Network
      Section 7 : Cluster Generation
28
Cluster Generation
29
Cluster Generation Output Analysis
      Section 8 : Decision Trees
30
Decision Trees of Machine Learning
31
Car Evaluation Problem Statement
32
Plotting a Decision Tree
33
Prediction Analysis- Decision Tree
      Section 9 : Text Mining
34
Introduction to Text Mining
35
Text Mining with R

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