Artificial Intelligence | What is AI | Introduction to
Artificial Intelligence |
Artificial intelligence the next big thing but why do we need I hear is a lot
lying in his grade let's go back into time and see what happened. Alan met
with a major accident because of driving back home trunk along with
10,000 265 other people the same year every year this number is
increasing. We need an intelligent machine which has the power to think
analyze and make decisions this is nothing but artificial intelligence. The
most famous programming language is pipeline and tensor flow is a
Python package for implementing deep learning products so come and
master the concepts of AI and deep learning with Eddy Rekha structured
program of which deep learning models give very high accuracy for deep
learning. The program is a structured program which includes networks
convolutional neural networks neural networks recurrent neural networks.
networks RBM and auto encoders using tensor.
Zulaikha from Edureka will be covering all the domains and concepts involved
under the umbrella of artificial intelligence. She will also be showing you a couple
of use cases and practical implementations by using Python. So there 's a lot to
cover in this session, and let me quickly run you through today's agenda. 1950 was
speculated to be one of the most important years for the introduction of artificial
intelligence. In 1950, Alan Turing published a paper in which he speculated about
the possibility of creating machines that think. Alan Turing created what is known
as the Turing test. This test is used to determine whether or not a computer can
think intelligently like a human being. AI started off as a hypothetical situation.
Right now it 's the most important technology in today 's world. Everything around
us is run through AI deep learning or machine learning. AI covers domains such as
machine learning, deep learning, neural networks, natural language processing,
knowledge based systems and so on.
AI is rapidly growing both as a field of study and also as an economy. The term
artificial intelligence was first coined in the year 1956 by John McCarthy at the
Dartmouth Conference. AI is the theory and development of computer systems able
to perform tasks that normally require human intelligence. In a sense, AI is a
technique of getting machines to work and behave like humans. AI has reach a
stage wherein it can compute the most complex of complex problems in a matter
of seconds. Even though AI can not think and reason like humans but their
, computational power is very strong compared to humans. IBM Watson technology
was able to cross reference 20 million oncology records quickly and correctly
diagnose a rare leukemia condition in a patient. AI implements computer vision,
image detection, deep learning to build cars that can automatically det ect any
objects or any obstacles and drive around without human intervention. Netflix uses
AI to create a personalized movie recommendation engine for each of its users.
Apart from Netflix, Gmail also uses AI on a everyday basis to classify emails as spam
and non-spam
Ray Shamar from Madeo Rica takes you through a very interesting topic that is
none other than deep learning. He explains how deep learning is a subfield of
artificial intelligence and how it is achieved by mimicking a human brain by
understanding how it thinks how it learns and work while trying to solve a problem.
Machine learning is a subset of artificial intelligence which provides computers with
the ability to learn without being explicitly programmed in machine learning. The
idea behind deep neural networks is not new but it dates back to 1950s however it
became possible to practically implement it only when we have the new high end
resource capability. Machine learning was not capable of solving the few cases and
hence deep learning came to the rescue the deep learning is capable of handling
the high dimensional data and is efficient in focusing on the right features on its
own and this process is called feature extraction. Deep learning studies the basic
unit of the brain called a brain cell or anula in an attempt to re-engineer a human
brain.
A deep network will be created with multiple hidden layers to process all the 50,000
images pixel by pixel and finally will receive an output so the output will be an
array of index 0 to 9 where each index corresponds to the respective digits. In order
to completely train this model it is going to take 20,000 steps let me show you in
the code. Program flow so here it is then here I have the steps to 20,000 but you
can always configure it to a number that is thousand two thousand. However you
have to run this code for n number of times so that you can achieve a particular
accuracy. After executing for twenty thousand times what happens as a model is
created with an accuracy of 92 % so what does it mean it means it means that if
you follow the particular image out of one hundred images of the model 92
predictions will be correct 92 of times this model will be able to tell you the exact
number. Facebook is able to Auto tag it is not only able to detect fac es but also
identify who it is and how is this possible it is only possible using deep learning.
Facebook also has a deep learning library called cafe - using which they has applied
all these things the next few case that is implemented using deep. learnin g is
Artificial Intelligence |
Artificial intelligence the next big thing but why do we need I hear is a lot
lying in his grade let's go back into time and see what happened. Alan met
with a major accident because of driving back home trunk along with
10,000 265 other people the same year every year this number is
increasing. We need an intelligent machine which has the power to think
analyze and make decisions this is nothing but artificial intelligence. The
most famous programming language is pipeline and tensor flow is a
Python package for implementing deep learning products so come and
master the concepts of AI and deep learning with Eddy Rekha structured
program of which deep learning models give very high accuracy for deep
learning. The program is a structured program which includes networks
convolutional neural networks neural networks recurrent neural networks.
networks RBM and auto encoders using tensor.
Zulaikha from Edureka will be covering all the domains and concepts involved
under the umbrella of artificial intelligence. She will also be showing you a couple
of use cases and practical implementations by using Python. So there 's a lot to
cover in this session, and let me quickly run you through today's agenda. 1950 was
speculated to be one of the most important years for the introduction of artificial
intelligence. In 1950, Alan Turing published a paper in which he speculated about
the possibility of creating machines that think. Alan Turing created what is known
as the Turing test. This test is used to determine whether or not a computer can
think intelligently like a human being. AI started off as a hypothetical situation.
Right now it 's the most important technology in today 's world. Everything around
us is run through AI deep learning or machine learning. AI covers domains such as
machine learning, deep learning, neural networks, natural language processing,
knowledge based systems and so on.
AI is rapidly growing both as a field of study and also as an economy. The term
artificial intelligence was first coined in the year 1956 by John McCarthy at the
Dartmouth Conference. AI is the theory and development of computer systems able
to perform tasks that normally require human intelligence. In a sense, AI is a
technique of getting machines to work and behave like humans. AI has reach a
stage wherein it can compute the most complex of complex problems in a matter
of seconds. Even though AI can not think and reason like humans but their
, computational power is very strong compared to humans. IBM Watson technology
was able to cross reference 20 million oncology records quickly and correctly
diagnose a rare leukemia condition in a patient. AI implements computer vision,
image detection, deep learning to build cars that can automatically det ect any
objects or any obstacles and drive around without human intervention. Netflix uses
AI to create a personalized movie recommendation engine for each of its users.
Apart from Netflix, Gmail also uses AI on a everyday basis to classify emails as spam
and non-spam
Ray Shamar from Madeo Rica takes you through a very interesting topic that is
none other than deep learning. He explains how deep learning is a subfield of
artificial intelligence and how it is achieved by mimicking a human brain by
understanding how it thinks how it learns and work while trying to solve a problem.
Machine learning is a subset of artificial intelligence which provides computers with
the ability to learn without being explicitly programmed in machine learning. The
idea behind deep neural networks is not new but it dates back to 1950s however it
became possible to practically implement it only when we have the new high end
resource capability. Machine learning was not capable of solving the few cases and
hence deep learning came to the rescue the deep learning is capable of handling
the high dimensional data and is efficient in focusing on the right features on its
own and this process is called feature extraction. Deep learning studies the basic
unit of the brain called a brain cell or anula in an attempt to re-engineer a human
brain.
A deep network will be created with multiple hidden layers to process all the 50,000
images pixel by pixel and finally will receive an output so the output will be an
array of index 0 to 9 where each index corresponds to the respective digits. In order
to completely train this model it is going to take 20,000 steps let me show you in
the code. Program flow so here it is then here I have the steps to 20,000 but you
can always configure it to a number that is thousand two thousand. However you
have to run this code for n number of times so that you can achieve a particular
accuracy. After executing for twenty thousand times what happens as a model is
created with an accuracy of 92 % so what does it mean it means it means that if
you follow the particular image out of one hundred images of the model 92
predictions will be correct 92 of times this model will be able to tell you the exact
number. Facebook is able to Auto tag it is not only able to detect fac es but also
identify who it is and how is this possible it is only possible using deep learning.
Facebook also has a deep learning library called cafe - using which they has applied
all these things the next few case that is implemented using deep. learnin g is
