This document is a student paper on applications of machine learning. It defines machine learning and compares normal computers to machine learning systems. It discusses machine learning algorithms like neural networks and decision trees. It describes the three main types of machine learning as supervised learning, unsupervised learning, and reinforcement learning. Examples of machine learning applications are given like traffic prediction, virtual assistants, and spam filtering. Popular programming languages for machine learning are listed along with examples of machine learning in practice and the advantages and disadvantages of machine learning.

1. DR. B C ROY ENGINEERING
COLLEGE DURGAPUR
NAME: NITISH KUMAR
ROLL NO.: 12001319032
SEMESTER: 7TH
DEPARTMENT: CSE2 (GROUP-Y)
PAPER NAME: MACHINE LEARNING
PAPER CODE: PEC-CS 701E
Title - Applications of Machine Learning

2. 2/23/2023
CONTENT
 Machine Learning
 Normal Computer vs ML
 Machine learning algorithms
 Types of Machine Learning
 Machine Learning Applications
 Real Time Examples for ML
 Programming Languages for ML
 Difference Between ML And AI
 Advantages of Machine Learning
 Disadvantages of Machine Learning

3. What is Machine Learning
• Machine learning is an application of artificial
intelligence that involves algorithms and data
that automatically analyse and make decision
by itself without human intervention.
• It describes how computer perform tasks on
their own by previous experiences.
• Therefore we can say in machine language
artificial intelligence is generated on the basis
of experience.
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4. Normal Computer vs. ML
• The difference between normal computer
software and machine learning is that a
human developer hasn’t given codes that
instructs the system how to react to situation,
instead it is being trained by a large number of
data.
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Some of the machine learning algorithmsare:
• Neural Networks
• Random Forests
• Decision trees
• Genetic algorithm
• Radial basis function
• Sigmoid

6. Types of Machine Learning
There are three types of machine learning
– Supervised learning
– Unsupervised learning
– Reinforcement learning

7. Machine Learning Applications:
• Traffic prediction
• Virtual Personal Assistant
• Speech recognition
• Email spam and malware filtering
• Bioinformatics
• Natural language processing
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8. Real Time Examples for ML
• TRAFFIC PREDICTION
• VIRTUAL PERSONAL ASSISTANT
• ONLINE TRANSPORTATION
• SOCIAL MEDIA SERVICES
• EMAIL SPAM FILTERING
• PRODUCT RECOMMENDATION
• ONLINE FRAUD DETECTION
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9. Best Programming Languages for
ML
Some of the best and most commonly used machine learning programs are
• Python,
• java,
• C,
• C++,
• Shell,
• R,
• JavaScript,
• Scala
• Shell,
• Julia
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10. Difference Between Machine Learning And Artificial
Intelligence
• Artificial Intelligence is a concept of creating
intelligent machines that stimulates human
behaviour whereas Machine learning is a
subset of Artificial intelligence that allows
machine to learn from data without being
programmed.
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11. Advantages of Machine Learning
• Fast, Accurate, Efficient.
• Automation of most applications.
• Wide range of real life applications.
• Enhanced cyber security and spam detection.
• No human Intervention is needed.
• Handling multi dimensional data.
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12. Disadvantages of Machine Learning
• It is very difficult to identify and rectify the
errors.
• Data Acquisition.
• Interpretation of results Requires more time
and space.
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13. THANK YOU
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