A

SEMINAR REPORT
ON

Artificial Intelligence and Machine Learning

(BCA-206)
In the partial fulfillment for the award of Bachelor of Computer Application (BCA)
(Session 2022-2025)

Submitted By: Submitted To:

Vrinda (1322425) Dr. Neha Goyal
Aarya (1322445) (Associate Professor)
BCA-2nd Sem.(F)

MM INSTITUTE OF COMPUTER TECHNOLOGY AND BUSINESS MANAGEMENT

Maharishi Markandeshwar (DEEMED TO BE UNIVERSITY)
(Established under Section 3 of UGC Act, 1956)
(Accredited by NAAC with Grade A++)
 CONTENT
1. What is Artificial Intelligence?
2. Why is Artificial Intelligence important?
3. Advantages and Disadvantages of AI
4. Applications of AI
5. What is Machine Learning?
6. Need of Machine Learning
7. Applications of Machine Learning
8. AI vs ML
9. Conclusion
 WHAT IS ARTIFICIAL INTELLIGENCE

• Artificial intelligence is a field of science concerned with

building computers and machines that can reason, learn,
and act in such a way that would normally require
human intelligence or that involves data whose scale
exceeds what humans can analyze.
• AI is a broad field that encompasses many different
disciplines, including computer science, data analytics
and statistics, hardware and software engineering,
linguistics, neuroscience, and even philosophy and
psychology.
• On an operational level for business use, AI is a set of
technologies that are based primarily on machine
learning and deep learning, used for data analytics,
predictions and forecasting, object categorization,
natural language processing, recommendations,
intelligent data retrieval, and more.
 WHY IS AI IMPORTANT
AI is important for its potential to change how we live, work
and play. It has been effectively used in business to automate
tasks done by humans, including customer service work, lead
generation, fraud detection and quality control. In a number
of areas, AI can perform tasks much better than humans.
Particularly when it comes to repetitive, detail-oriented tasks,
such as analyzing large numbers of legal documents to ensure
relevant fields are filled in properly, AI tools often complete
jobs quickly and with relatively few errors. Because of the
massive data sets it can process, AI can also give enterprises
insights into their operations they might not have been aware
of. The rapidly expanding population of generative AI
tools will be important in fields ranging from education and
marketing to product design.
 ADVANTAGES OF AI

1. AI-powered virtual agents are always available

2. Saves labor and increases productivity
3. Delivers consistent results
4. Can improve customer satisfaction through personalization
5. Good at detail-oriented jobs

DISADVANTAGES OF AI

1. Expensive
2. Limited supply of qualified workers to build AI tools
3. Requires deep technical expertise
4. Eliminates human jobs, increasing unemployment rates
5. Lack of ability to generalize from one task to another
 APPLICATIONS OF AI
1. AI in entertainment and media. The entertainment business
uses AI techniques for targeted advertising, recommending
content, distribution, detecting fraud, creating scripts, and
making movies. Automated journalism helps newsrooms
streamline media workflows reducing time, costs, and
complexity.
2. AI in law. Using AI to help automate the legal industry's labor-
intensive processes is saving time and improving client service.
Law firms use machine learning to describe data and predict
outcomes, computer vision to classify and extract information
from documents, and NLP to interpret requests for information.
3. AI in healthcare. The biggest bets are on improving patient
outcomes and reducing costs. Companies are applying machine
learning to make better and faster medical diagnoses than
humans. One of the best-known healthcare technologies is IBM
Watson. It understands natural language and can respond to
questions asked of it.
4. AI in education. AI can automate grading, giving educators
more time for other tasks. It can assess students and adapt to
their needs, helping them work at their own pace. AI tutors can
provide additional support to students, ensuring they stay on
track. Technology could also change where and how students
learn.
WHAT IS MACHINE LEARNING
• Machine learning is a growing technology that enables
computers to learn automatically from past data. Machine
learning uses various algorithms for building mathematical
models and making predictions using historical data or
information. Currently, it is being used for various tasks such
as image recognition, speech recognition, email
filtering, Facebook auto-tagging, a recommender system, and
many more.
• Machine Learning is said as a subset of artificial
intelligence that is mainly concerned with the development of
algorithms that allow a computer to learn from the data and
past experiences on their own.
• With the help of sample historical data, which is known
as training data, machine learning algorithms build
a mathematical model that helps in making predictions or
decisions without being explicitly programmed. Machine
learning brings computer science and statistics together for
creating predictive models. Machine learning constructs or uses
the algorithms that learn from historical data. The more we will
provide the information, the higher will be the performance.
NEED OF MACHINE LEARNING

• The need for machine learning is increasing day by day. The

reason behind the need for machine learning is that it is
capable of doing tasks that are too complex for a person to
implement directly. As a human, we have some limitations as
we cannot access a huge amount of data manually, so for this,
we need some computer systems, and here comes machine
learning to make things easy for us.
• We can train machine learning algorithms by providing them a
huge amount of data and letting them explore the data,
construct the models, and predict the required output
automatically. The performance of the machine learning
algorithm depends on the amount of data, and it can be
determined by the cost function. With the help of machine
learning, we can save both time and money.
• The importance of machine learning can be easily understood
by its uses cases, Currently, machine learning is used in self-
driving cars, cyber fraud detection, face recognition,
and friend suggestion by Facebook, etc. Various top companies
such as Netflix and Amazon have built machine learning models
that are using a vast amount of data to analyze user interest
and recommend products accordingly.
APPLICATIONS OF MACHINE LEARNING

1. Image Recognition:
Image recognition is one of the most common applications of
machine learning. It is used to identify objects, persons, places,
digital images, etc. The popular use case of image recognition and
face detection is, Automatic friend tagging suggestion:
Facebook provides us with a feature of an auto friend tagging
suggestions. Whenever we upload a photo with our Facebook
friends, then we automatically get a tagging suggestion with a
name, and the technology behind this is machine learning's face
detection and recognition algorithm.
2. Speech Recognition:
While using Google, we get an option of "Search by voice," which
comes under speech recognition, and it's a popular application of
machine learning.
Speech recognition is a process of converting voice instructions
into text, and it is also known as "Speech to text", or "Computer
speech recognition." At present, machine learning algorithms are
widely used in various applications of speech recognition. Google
Assistant, Siri, Cortana, and Alexa are using speech recognition
technology to follow voice instructions.
3. Traffic prediction:
If we want to visit a new place, we take the help of Google Maps,
which shows us the correct path with the shortest route and
predicts the traffic conditions.
It predicts the traffic conditions such as whether traffic is cleared,
slow-moving, or heavily congested with the help of two ways:
• Real Time location of the vehicle from Google Map app and
sensors
• Average time taken on past days at the same time.
Everyone who is using Google Maps is helping this app to make it
better. It takes information from the user and sends it back to its
database to improve performance.
4. Product recommendations:
Machine learning is widely used by various e-commerce and
entertainment companies such as Amazon, Netflix, etc., for
product recommendations to the user. Whenever we search for
some product on Amazon, then we started getting an
advertisement for the same product while internet surfing on the
same browser and this is because of machine learning.
5. Self-driving cars:
One of the most exciting applications of machine learning is self-
driving cars. Machine learning plays a significant role in self-driving
cars. Tesla, the most popular car manufacturing company is
working on self-driving cars. It is using unsupervised learning
method to train the car models to detect people and objects while
driving.
 AL vs ML
Artificial Intelligence Machine learning

Artificial intelligence is a Machine learning is a subset of

technology which enables a AI which allows a machine to
machine to simulate human automatically learn from past
behavior. data without programming
explicitly.
The goal of AI is to make a The goal of ML is to allow
smart computer system like machines to learn from data so
humans to solve complex that they can give accurate
problems. output.
Machine learning and deep Deep learning is a main subset
learning are the two main of machine learning.
subsets of AI.
AI has a very wide range of Machine learning has a limited
scope. scope.
AI is working to create an Machine learning is working to
intelligent system which can create machines that can
perform various complex tasks. perform only those specific
tasks for which they are
trained.
The main applications of AI The main applications of
are Siri, customer support machine learning are Online
using catboats, Expert System, recommender system, Google
Online game playing, intelligent search algorithms, Facebook
humanoid robot, etc. auto friend tagging
suggestions, etc.
 CONCLUSION
Artificial Intelligence and technology are one side of life
that always interest and surprises us with new ideas,
topics, innovations, products …etc. AI is still not
implemented as the films representing it(i.e. intelligent
robots), however, there are many important tries to reach
the level and to compete in the market, like sometimes the
robots that they show on TV. Nevertheless, the hidden
projects and the development in industrial companies.
In the end, we’ve been in this research through the AI
definitions, brief history, applications of AI in public,
applications of AI in the military, ethics of AI, and the three
rules of robotics. This is not the end of AI, there is more to
come from it, who knows what AI can do for us in the
future, maybe it will be a whole society of robots.