Comparison Between Artificial Intelligence, Machine Learning, and Deep Learning
Comparison between Artificial Intelligence, Machine Learning, and Deep
Presently, Artificial Intelligence is extensively used in almost all the business industries. It is a science
and engineering of developing an intellectual framework and we can say it is the future of almost all
the business industries. Artificial intelligence has turn into the critical part of our daily routine. It is
used in several applications such as speech recognition, video games, smart cars, fraud detection,
etc. Along with artificial intelligence, machine learning, and deep learning have the essential part of
various businesses. Nowadays, everyone is familiar with all these words. The term artificial
intelligence, machine learning and deep learning are normally used randomly and conversely. They
all are nearly associated with each other, however, have a few contrasts. This post presents a
comparison between deep learning, machine learning and artificial intelligence. Let us have a look at
the below image.
The image shows that deep learning is a subgroup of machine learning and machine learning is a
subgroup of artificial intelligence. Moreover, we can say that artificial intelligence is the parent of
machine learning and deep learning.
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Artificial intelligence is basically the branch of computer science which deals with the modeling of
intelligent behavior in the computer system. We can say it is the skill of making the smart computer
to mimic the human behavior. It makes the computer system smart in such a way that, it is able to
finish the tasks which are usually carried out by humans, such as speech recognition, decision-
making, visual perception and transformation between languages. Artificial intelligence can be
accomplished by understanding how the human brain thinks, how human acquires the knowledge,
how they adapt and work when they are trying to solve a particular problem and on the basis of the
result of this study an intelligent software system can be developed. The applications of artificial
intelligence allow the machines to carry out various human tasks with specific improved skills. As
present age is the age of big data which makes the use of AI more important. With the increase of
data in a business and the continuous birth of new data, it will be impossible for the human being to
think, sort, analyze, evaluate and reach a fruitful decision. Well, there are two main objectives of the
artificial intelligence – first is to develop the expert systems, i.e., the systems which are able to show
the behavior, learn, explain and give guidance to its users and the second is to implement the brain
of human in machines i.e. developing a system in such a way that understand, think, act and learn
like the humans. In this real world, the knowledge contains some unwanted properties such as huge
volume, not well-organized and well-formatted and its continuous changing status. With the help of
AI methods these properties can be organized in a proper way and utilize the knowledge proficiently
in such a manner that:
• It should be easily adaptable to correct the errors.
• It should be beneficial in certain situations however it is imprecise or incomplete.
With the help of these AI techniques the speed of execution of the complicated program can be
Applications of Artificial Intelligence:
The artificial intelligence can be used in various fields such as:
1. Natural Language Processing: With the help of AI, it is possible to intermingle with the computer
that only understand the natural language of the humans.
2. Gaming: AI plays an important role in planned games such as chess, poker, etc. where the
machine is capable of thinking the various possible situations based on experimental knowledge.
3. Speech recognition: With the help of AI, some intelligent systems are able to hear and understand
the language in terms of sentences and their significance. It is capable of managing various
pronunciations, jargon words, some alteration in human’s voice, and background sound etc.
4. Handwriting recognition: This software is capable of reading the text written on paper using a
pen. It is capable of identifying the shapes of the letters and convert it into editable text.
5. Also the application of AI can be seen in the field of vision systems and intelligent robot. With the
help of vision systems it is easy to understand, interpret the visual inputs given to the computer. And
the intelligent robots are capable of performing the tasks provided by the human.
Advantages of Artificial Intelligence:
There are several advantages of using artificial intelligence, which assist the humans to carry out
various difficult and monotonous tasks. The AI machines can work continuously without any break.
Let us now observe some of the benefits of AI.
1. With the help of AI, the human participation in particular jobs is reduced.
2. The AI machines are capable of performing the task, faster and quickly without any errors.
3. AI is used in the healthcare field as well. With the help of Artificial Intelligence,the doctors are
able to carry out long medical processes efficiently, and also the researchers can get the feedback
easily related to the side effects of various medications.
4. These machines can perform the task continuously 24 by 7 without any break and relaxation. This
is the biggest advantage of AI over humans.
5. With the utilization of AI our life has become much easier.
It is known to us that machine learning is the subset of artificial intelligence. We can say that it is the
succeeding logical step in AI. The basic idea in machine learning is about creating algorithms, which
produces some output values based on some input values using the statistical analysis. It aims to
search, the pattern in a huge amount of data and takes the necessary actions accordingly. It is
basically a technique of data analytics that elucidates the computers to perform the tasks based on
the previous experience. Machine learning is an extension of artificial intelligence which is based on
the fact that the systems can acquire knowledge from the data, recognize patterns and make
decisions without human involvement. The main objective of the machine learning is to recognize
the data structure and apt that particular data into models which can be easily understood and used
by the people. The machine learning algorithms allow the computers to get trained on provided data
inputs and utilized statistical analysis to provide the output values within a particular series. Due to
this, the computer can create models using the sample data so that the decision-making processes
can be automated easily which are based on the data inputs. There are two types of machine
learning, i.e. supervised and unsupervised learning.
Application of Machine Learning:
Similar to artificial intelligence, the machine learning techniques also have several applications. Few
of them are:
1. Machine learning is used in the field of marketing and sales to analyze the sales history and
promote other items.
2. It is used in banking and other financial services to detect the frauds.
3. It is used in transportation and education.
4. Machine learning can also be used in the field of automatic speech and image recognition and
natural language processing.
5. It is used in the healthcare industry, with the help of its sensors and wearable devices the
patient’s health can be measured in existent time.
6. Machine learning is used by search engines to enhance their services.
Advantages of Machine Learning:
Machine learning has provided several benefits to the user, such as:
1. Machine learning allows the reduction in time cycle and provides efficient resource utilization.
2. It has the capacity to manage multi-dimensional and variety of data in the dynamic and unreliable
3. There are some tools which are available to provide the constant quality enhancement in large
and complex process environments.
4. The usability of algorithms for several applications can be increased with the help of the source
As machine learning is the subset of AI, similarly deep learning is the subset of machine learning. In
order to carry out machine learning tasks in multiple ways, deep learning uses a series of algorithms.
Deep learning depends on the artificial neural network’s framework which needs a lot of
computational power to learn and have various layers inserted in it. As there exist many deep layers
of learning, so it leads to the name deep learning. It requires a huge amount of data sets and can
become more expensive. Deep learning has the capacity to analyze and judge the information to
reach a logical decision, and define solutions and learn from errors. Thus if a machine receives more
data, then it is more capable of learning.
Application of Deep Learning:
Deep learning also has several applications, some of them are:
1. Similar to machine learning, deep learning is also used in the healthcare industry.
2. It is used in voice search and voice-activated intelligent supporters.
3. It is used to add sound automatically to the silent movies.
4. Deep learning is also used in the automatic transformation of text and pictures.
5. The other applications are predicting earthquakes, advertising, and automatic colorization.
Advantage of Deep Learning:
Deep learning has one major advantage over machine learning algorithm that it is able to produce
new features without human involvement from the partial series of features which are placed in the
training data set. With the help of these new features, a lot of time of data scientist can be saved on
working with big data and dependency on this particular technology.
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Thus, artificial intelligence, machine learning and deep learning can be used conversely. The artificial
intelligence is a wider concept, that addresses the use of computers to imitate the intellectual
functions of human. Artificial intelligence is divided into three categories, narrow AI to carry out a
particular task, artificial general intelligence that can mimic the thinking of a human and super-
intelligent AI, in which the AI exceed the intelligence of humans. Machine learning is a subset of
Artificial intelligence which shows its most fruitful use cases. It includes learning from data to make a
proficient decision and allows an AI to be applied to a wide range of problems. On the other hand
deep learning is a subset of machine learning. In order to train the models on a huge set of data it
employs the power of neural network and also it makes the exact predictions in various fields such
as image, face and voice recognition.
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