This document provides an overview of machine learning, including definitions, when and where it can be used, its evolution, the learning process, types of learning, applications in industry, and job opportunities. It defines machine learning as a field that gives computers the ability to learn without being explicitly programmed by improving performance on tasks through experience. Examples are given of when machine learning is useful, such as when human expertise does not exist or models need to be customized. The learning process and main types of learning - supervised, unsupervised, and reinforcement learning - are also outlined.

1. BASICS OF MACHINE LEARNING AND
ITS INDUSTRIAL IMPORTANCE
Mrs. Nagarathna C
Asst Prof. CSE, SKIT

2. FLOW OF PRESENTATION
 Definitions
Learning
Machine Learning (ML)
 When and Where to use ML
 Evolution of ML
 Learning Process
 Types of Learning
 Industry Application
 Job Opportunities
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3. EXERCISE-1
WRITE AS MANY WORDS AS YOU CAN READ

4. ANSWER BELOW QUESTIONS
 How many words did you notice/see?
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 How many words did you
write?
 How many words did you remember
more?

5. DEFINITIONS
 Learning: It is a process by which a system
improves performance from experience.
– Herbert Simon
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 Machine Learning: Field of study that gives computers
the ability to learn without being explicitly programmed.
– Arther Samuel
 Machine Learning: It is the study of algorithms that
improves their performance <P>, at some task <T> with
experience <E>. A well defined learning task its given by
<P,T,E>
– Tom Mitchell

6.  Traditional Programming
COMPUTER
INPUT
PROGRAM OUTPUT
COMPUTER
 Machine Learning
INPUT
OUTPUT
PROGRAM
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7. WHEN AND WHERE TO USE ML
1. Human expertise does not exist
Mars’ mission
2 . Human can’t explain their expertise
Speech recognition
3. Models can be customized
Medicines
4. Models are based on huge amount of data
genomics
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8. EVOLUTION
Image: Linked In | Machine Learning vs Deep learning
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9. KEYPOINTS TO REMEMBER
 Machine Learning works for monotonous task
 As knowledge tuned to specific task
 Is our brain multitask of
monotasked?
Hand rotation exercise
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10. WHY ITS IS BEST TIME FOR ML
 System are now flooded with data
 Increase in computational power
 Growing progress is available algorithms and
theory developed by researchers
 Increasing acceptance and support from
industries
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11. THE LEARNING PROCESS
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12. Types of Learning
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13. Supervised machine learning
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14. Unsupervised machine learning
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15. Reinforcement machine learning
In this, the machine learns from a hit and trial method.
Whenever the model predicts or produces a result, it is
penalized if the prediction is wrong or rewarded if the
prediction is correct. Based on these actions the model
trains itself.
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16. Applications of Machine
learning
Virtual Personal Assistant
Facial recognition
E-mail spam filter
Recommendation engine on an e-commerce
website
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17. Job Opportunities in ML
• Data Scientists
• Data Mining and Analysis
• Machine Learning Engineer
• AI Engineer
• Business Intelligence (BI) Developer
• Robotics programmer
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18. 18 / 19

19. “TorTure The daTa, and iT wilL confess To anyThing.”
– Ronald Coase
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