This describes the supervised machine learning, supervised learning categorisation( regression and classification) and their types, applications of supervised machine learning, etc.

1. Supervised Machine Learning
BY:
ANKIT RAI

2. Why it is called Supervised Learning ?
• It is called supervised learning because the process of an algorithm learning
from the training dataset can be thought of as a teacher supervising the
learning process.
• We know the correct answers, the algorithm iteratively makes predictions
on the training data and is corrected by the teacher.
• Learning stops when the algorithm achieves an acceptable level of
performance

3. What actually happens in
Supervised Machine Learning ?

4. What actually happens here ?
• In supervised learning, we train our model on a labelled dataset ( we have
raw data as well as its result )
• We split our data into a training dataset and test dataset
• Training dataset is used to train our network
• Testing dataset acts as new data for predicting results or to see the accuracy
of our model

5. Supervised Machine Learning Categorisation
• Classification Models
• Regression Models

6. Classification Models
• Classification models are used for problems
where the output variable can be categorized,
such as “Yes” or “No”, or “Pass” or “Fail”.
• Classification Models are used to predict the
category of the data.

7. Regression Models
• Regression models are used for problems
where the output variable is a real value such
as a unique number, dollars, salary, weight or
pressure, for example.
• It is most often used to predict numerical
values based on previous data observations.

8. Types :
• Regression
• Logistic Regression
• Classification
• Naïve Bayes Classifiers
• DecisionTrees
• SupportVector Machine

9. Application of Supervised Machine Learning
oSentiment Analysis
It is a natural language processing technique in which we analyze and
categorize some meaning out of the given text data. For example, if we are
analyzing tweets of people and want to predict whether a tweet is a query,
complaint, suggestion, opinion or news, we will simply use sentiment analysis.

10. oRecommendations
Every e-Commerce site or media, all of them use the recommendation system
to recommend their products and new releases to their customers or users on
the basis of their activities. Netflix, Amazon,Youtube, Flipkart are earning
huge profits with the help of their recommendation system.

11. oSpam Filtration
Detecting spam emails is indeed a very helpful tool, this filtration techniques
can easily detect any sort of virus, malware or even harmful URLs. In recent
studies, it was found that about 56.87 per cent of all emails revolving around
the internet were spam in March 2017 which was a major drop fromApril
2014's 71.1 per cent spam share.