Comparison between Artificial Intelligence, Machine Learning, and Deep LearningCategory: AI & Machine Learning, ZaranTech Training Posted:Jun 08, 2018 By: Robert
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.
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 raised.
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 environment.
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 program.
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.
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.