Machine Learning and its types - Internship Presentation - week 8 What is AI, ML & DL What is Machine Learning? How do Machine Learn? Types of Machine Learning Major Machine Learning Techniques

1. WEEKLY PRESENTATION
DURING TRAINING PROGRAM
- Devang Garach
devanggarach.rao@gmail.com
WEEK-8
Information Technology Pvt. Ltd.
MACHINE LEARNING

2. OBJECTIVES - MACHINE LEARNING
What is AI, ML & DL
What is Machine Learning?
How do Machine Learn?
Types of Machine Learning
Major Machine Learning Techniques
Information Technology Pvt. Ltd.
MACHINE LEARNING

3. What is AI, ML & DL
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MACHINE LEARNING
Source : edureka.co

4. What is Machine Learning
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MACHINE LEARNING
Machine Learning is a subset of artificial intelligence. It focuses mainly on
the designing of systems, thereby allowing them to learn and make
predictions based on some experience which is data in case of machines.

5. How do Machine Learn?
Information Technology Pvt. Ltd.
MACHINE LEARNING
ML Process can be divided into 3 sequential parts:
DATA INPUT
Past data or information which is utilize as a basis for future decision making(prediction).
ABSTRACTION
The Input data is processed using underlying algorithm.
ABSTRACTION helps in deriving a "CONCEPTUAL MAP/MODEL" based on input data.
The model may be in any one of the following form:
(1) A Block of "IF...ELSE..." rule
(2) Mathematical Equations
(3) A Data structure like TREE/GRAPH
(4) Logical Grouping of Similar Observations

6. How do machine learn?
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MACHINE LEARNING
GENERALIZATION
The abstract representation is generalized to form a framework for making
decisions.
The model is trained based on finite set of data which may have limited set
of characteristics.
To apply the model,to take decision on "set of UNKNOWN DATA(Testing
Data)" .
InputData ---> Abstraction ---> Generalization

7. Types of Machine Learning
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MACHINE LEARNING
● Supervised Learning
● Unsupervised Learning
● Reinforcement Learning

8. Types of Machine Learning
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MACHINE LEARNING
Supervised Learning:
Also known as "PREDICTIVE LEARNING" where a MACHINE predicts the
class of unknown objects based on previous class related information of
similar objects.
Major objective is to learn from previous information.
Example:
Separating images by either shape or color.

9. Types of Machine Learning
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MACHINE LEARNING
Supervised Learning (Continue...)
How machine is able to differentiate between different shapes?
Some information needs to be provided so that machine will understand
different shapes(TRAINING).
Providing information to machine is known as "TRAINING DATA" which is a
past information on specific task.
Along with features a tag is also provided,tag is called "LABEL".
In case of supervised learning, "TRAINING DATA ARE LABELED".

10. Types of Machine Learning
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MACHINE LEARNING
Supervised Learning (Continue...)
Source : edureka.co

11. Types of Machine Learning
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MACHINE LEARNING
Supervised Learning (Continue...)
Examples:
Predicting the result of a game.
Predicting whether tumour is malignant or benign.
Predicting the price of domain like real estate, stock-market Etc.
Classified text such as whether email is spam or not.
NOTE: If training data are of poor quality than prediction will not be precise.

12. Types of Machine Learning
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MACHINE LEARNING
Unsupervised Learning:
It is also known as "DESCRIPTIVE LEARNING" where machine finds a
pattern in unknown object by grouping similar objects together. In this,there
is NO LABELED training data to learn from.
The objective is to take dataset as input and find 'NATURAL GROUPINGS' or
'PATTERNS' from dataset.
Therefore it is often known as "DESCRIPTIVE MODEL" and the process is
also referred as "PATTERN DISCOVERY" or "KNOWLEDGE DISCOVERY".

13. Types of Machine Learning
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MACHINE LEARNING
Unsupervised Learning (Continue...)
Source : edureka.co

14. Types of Machine Learning
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MACHINE LEARNING
Unsupervised Learning (Continue...)
Examples:
Market Basket Analysis
Recommendation System
Source : edureka.co

15. Types of Machine Learning
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MACHINE LEARNING
Reinforcement Learning:
A machine LEARN TO ACT its own to achieve given goals.
Machine often learns to do task autonomously.
The agent interacts with the environment and explores it by itself. The
primary goal of an agent in reinforcement learning is to improve the
performance by getting the maximum positive rewards.
It improves its performance by doing the task,
If it does successfully, A REWARD IS GIVEN else it gets PENALTY
The machine continuous this this process for the entire task which is known
as "REINFORCEMENT LEARNING".

16. Types of Machine Learning
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MACHINE LEARNING
Reinforcement Learning (Continue...)
Source : edureka.co

17. Types of Machine Learning
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MACHINE LEARNING
Reinforcement Learning (Continue...)
Examples:
SELF DRIVING CARS where critical information needs to be taken care like
speed and speed limit in different road segments, traffic conditions, road
conditions, weather condition Etc.
Source : edureka.co

18. Major Machine Learning Techniques
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MACHINE LEARNING
Regression / Estimation
Predicting continuous value
Classification
Predicting the item class/category of a case
Clustering
Finding the structure of data, summarization
Associations
Associating frequent co-occurring items / events

19. Major Machine Learning Techniques (Continue...)
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MACHINE LEARNING
Anomaly detection
Discovering abnormal and unusual cases
Sequence mining
Predicting next events
Dimension Reduction
Reducing the size of data (PCA)
Recommendation System
Recommending items

20. Thank You.
- Devang Garach
devanggarach.rao@gmail.com
Information Technology Pvt. Ltd.