Machine learning is a branch of artificial intelligence. In which computers study algorithms. If I say in simple terms, machine learning is a computer algorithm study method that allows computer programs to learn from their experience. Now the question arises what is the algorithm.
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2. CONTENTS
Why Machine learning?
Defining Machine Learning
Traditional Programming vs Machine
Learning
Application of Machine Learning
Process of Learning
Machine Learning Algorithm
Decision Learning
Machine Learning scope
Limitation Of Machine Learning?
Software
Conclusion
References
3. Why Machine
Learning?
Develop systems that can automatically
adapt and customize themselves to
individual users.
Discover new knowledge from large
databases (data mining).
Ability to mimic human and replace
certain monotonous tasks.
Develop systems that are too
difficult/expensive to construct
manually.
4. Defining
Machine
Learning.
Machine learning is a method of data
analysis that automates analytical
model building.
Machine learning (ML) is the study of
computer algorithms that improve
automatically through experience.
Machine learning algorithms build
mathematical model based on sample
data, known as "training data“.
Machine learning is closely related
to computational statistics.
Python language suitable for a variety
of tasks in machine learning.
5. Traditional Programming vs Machine
Learning
Traditional Programming
Data
Output
Program
Machine Learning
Data
Program
Program
Computer
Computer
11. Decision
Learning
Decision tree learning is one of the
predictive modeling approaches used
in machine learning.
A decision tree can be used to visually
and explicitly represent decisions and
decision making.
It uses a decision tree to go from
observations about an item to
conclusions about the item's target
value.
A decision tree is drawn upside down
with its root at the top.
12. Contd…
In the image on the left, the bold
text in black represents a
condition/internal node, based
on which the tree splits into
branches/ edges. The end of
the branch that doesn’t
split anymore is the decision/leaf, in
this case, whether the passenger
died or survived, represented as
red and green text
respectively.
13. Machine
Learning
Scope
Machine Learning in Search Engine
Defining Machine Learning
Traditional Programming vs Machine
Learning
Application of Machine Learning
Process of Learning
14. Limitation Of
Machine
Learning
Accuracy depends on training learning
which is not always available.
Have large Data sets requirements to
learn about various topics which may
be time taken and require various
resources.
A Machine cannot learn if there is no
data.
Performance Machine Learning
cannot be Guaranteed.
16. Conclusion
Machine learning is quickly growing
field in computer science.
It has applications in nearly every other
field of study.
It is already being implemented
commercially because machine
learning can solve problems too
difficult or time consuming for humans
to solve.
To describe machine learning in
general terms, a variety models are
used to learn patterns in data and
make accurate predictions based on
the patterns it observes.