Machine Learning With R | Machine Learning Algorithms | Data Science Training | Edureka

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Machine Learning with R

Data Science Certification Training www.edureka.co/data-science
Agenda
Understanding Machine Learning1
Applications of Machine Learning 2
Languages for Machine Learning3
Types of Machine Learning Algorithms 4
Implementing Machine Learning Algorithms
with R
5

Understanding Machine Learning

What is
this?

How about
this?

And this?

How do you
know all of
these are
fish?

Now, how will
a computer
identify it as
a fish?
Machine

Fish
Machine
Fish
Fish

New Data Machine
Fish
Result

Applications of Machine Learning

Languages for Machine Learning

Why R?
Open Source
Functional
Programming
Turing CompleteObject Oriented

Steps in Machine Learning

Step 1
Ingesting Data

Step 1 Step 2
Data Wrangling
Ingesting Data

Step 1 Step 2 Step 3
Data Wrangling
Ingesting Data Train Algorithm

Step 1 Step 2 Step 3 Step 4
Data Wrangling
Test Algorithm

Step 1 Step 2 Step 3 Step 4 Step 5
Data Wrangling
Test Algorithm
Evaluate Result

Types of Machine Learning

Types of Machine Learning Algorithms

Supervised Learning

Supervised Learning
Supervised learning
algorithm, learns
from a known
dataset(training set)
to make predictions

Supervised Learning
I need
Training to
perform well
in the test

Classification

Classification
Man Woman

Classification – Decision Tree
Root Node
Branch Node
Leaf Node
A path from root to
leaf represents
classification rules

Classification Demo
Car_Purchase Data-set

Regression

Regression
Function: Y=F(X)

Regression Demo
Diamonds Data-set

Unsupervised Learning

Unsupervised
learning algorithm
draws inferences
from data which does
not have labels

No training
required, we
can learn by
ourselves

Clustering
Data
Cluster 1
Cluster 2

Clustering Demo
Iris Data-set

Reinforcement Learning

Reinforcement
learning involves
learning ideal
behavior through a
reward feedback
system

Eat food, earn points!
Hit a monster, lose
life!

Real World Applications of Reinforcement Learning
Google’s Self Driving Car
Manufacturing Robots
Autonomous Flying
Helicopter

Machine Learning Case Study

Case Study on Pokémon Dataset

Problem Statement –Task 1
You are a Pokémon trainer who is
entering the Jhoto League and have to
select one fire, water and grass
Pokémon for your fight

Problem Statement(Regression)-Task 2
Now, that you have won Jhoto League,
you want to understand what are the
factors influencing a Pokémon's attack!

Problem Statement(Classification)-Task 3
Team Rocket is on a mission to end the
world and this time only the Legendary
Pokemons can save the world. So, go
ahead and catch all the Legendary
Pokemon

Tasks Performed
Data Wrangling
Regression
Classification
Select fire,
water and
grass
Pokémons
Find out
how does a
Pokemon’s
defence
influence it’s
aattack
Classify if
the
Pokémon is
legendary or
not

Summary

Machine Learning With R | Machine Learning Algorithms | Data Science Training | Edureka

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