Introduction to Machine Learning
Machine learning is a method of data analysis that automates analytical
model building. It is a branch of artificial intelligence based on the idea that
systems can learn from data, identify patterns and make decisions with minimal
human intervention.
Example: Image recognition, Speech recognition, Medical diagnosis, Statistical
arbitrage, Predictive analytics, etc.
Artificial Intelligence, Machine Learning and Deep Learning
Artificial Intelligence is defined as a program that exhibits cognitive
ability similar to that of a human being. It makes computers think like
humans and solve problems the way we do is one of the main tenets of
artificial intelligence.
Any computer program that shows characteristics, such as self-
improvement, learning through inference, or even basic human tasks,
such as image recognition and language processing, is considered to be a
form of AI.
The field of artificial intelligence includes within it the sub-fields of
machine learning and deep learning.
Deep Learning is a more specialized version of machine learning that
utilizes more complex methods for difficult problems.
,
,Definition of machine learning
Arthur Samuel, an early American leader in the field of computer gaming and
artificial intelligence, coined the term “Machine Learning” in 1959 while at
IBM.
He defined machine learning as “the field of study that gives computers the
ability to learn without being explicitly programmed.” However, there is no
universally accepted definition for machine learning. Different authors define
the term differently. We give below two more definitions.
1. Machine learning is programming computers to optimize a performance
criterion using example data or past experience. We have a model defined up to
some parameters, and learning is the execution of a computer program to
optimize the parameters of the model using the training data or past experience.
The model may be predictive to make predictions in the future, or descriptive to
gain knowledge from data, or both.
2. The field of study known as machine learning is concerned with the question
of how to construct computer programs that automatically improve with
experience
Definition of learning
A computer program is said to learn from experience E with respect to some
class of tasks T and performance measure P, if its performance at tasks T, as
measured by P, improves with experience E.
Examples :
i) Handwriting recognition learning problem
• Task T: Recognising and classifying handwritten words within images
• Performance P: Percent of words correctly classified
• Training experience E: A dataset of handwritten words with given classifications
, ii) A robot driving learning problem
• Task T: Driving on highways using vision sensors
Machine learning is a method of data analysis that automates analytical
model building. It is a branch of artificial intelligence based on the idea that
systems can learn from data, identify patterns and make decisions with minimal
human intervention.
Example: Image recognition, Speech recognition, Medical diagnosis, Statistical
arbitrage, Predictive analytics, etc.
Artificial Intelligence, Machine Learning and Deep Learning
Artificial Intelligence is defined as a program that exhibits cognitive
ability similar to that of a human being. It makes computers think like
humans and solve problems the way we do is one of the main tenets of
artificial intelligence.
Any computer program that shows characteristics, such as self-
improvement, learning through inference, or even basic human tasks,
such as image recognition and language processing, is considered to be a
form of AI.
The field of artificial intelligence includes within it the sub-fields of
machine learning and deep learning.
Deep Learning is a more specialized version of machine learning that
utilizes more complex methods for difficult problems.
,
,Definition of machine learning
Arthur Samuel, an early American leader in the field of computer gaming and
artificial intelligence, coined the term “Machine Learning” in 1959 while at
IBM.
He defined machine learning as “the field of study that gives computers the
ability to learn without being explicitly programmed.” However, there is no
universally accepted definition for machine learning. Different authors define
the term differently. We give below two more definitions.
1. Machine learning is programming computers to optimize a performance
criterion using example data or past experience. We have a model defined up to
some parameters, and learning is the execution of a computer program to
optimize the parameters of the model using the training data or past experience.
The model may be predictive to make predictions in the future, or descriptive to
gain knowledge from data, or both.
2. The field of study known as machine learning is concerned with the question
of how to construct computer programs that automatically improve with
experience
Definition of learning
A computer program is said to learn from experience E with respect to some
class of tasks T and performance measure P, if its performance at tasks T, as
measured by P, improves with experience E.
Examples :
i) Handwriting recognition learning problem
• Task T: Recognising and classifying handwritten words within images
• Performance P: Percent of words correctly classified
• Training experience E: A dataset of handwritten words with given classifications
, ii) A robot driving learning problem
• Task T: Driving on highways using vision sensors
