Artificial Intelligence vs Machine Learning vs Deep learning vs Data science- Clearing the Confusion

Artificial Intelligence vs Machine Learning vs Deep learning vs Data science

Technology has taken a giant leap and we are a witness to new and improved technologies that have made our life better. The advent of new technologies such as Artificial Intelligence, Data Science, Deep Learning, and Machine Learning has given a new meaning to our lives. All these buzzwords are quite familiar to the students from a technical background. However, common people are not actually aware of these terms and they should also know about these terms as these are the new trends in our technological era.

Artificial Intelligence

Coined in the year 1956, artificial intelligence is today’s age technology that has come to the forefront due to increased advanced algorithms, data volumes & improvements in storage and computing power.

In the year the 1950s research was done in order to explore the topics such as symbolic methods and problem-solving. US defense department took interest in this research and started training the computers to mimic the basic reasoning of humans.

This early research has given birth to formal and automation reasoning that exists today such as smart search systems and decision support systems which are designed to augment and complement human abilities.

Artificial Intelligence, today, is offering many valuable benefits to the men in a number of fields such as retail, healthcare and so on.

Importance of Artificial Intelligence

Artificial Intelligence is the science of machines and computers, that is in the act of developing intelligence like that of humans. In this advanced technology, the machines are capable of doing complex stuff that we are bound to do on a daily basis. So, as AI has been able to do such activities on a day to day basis, this technology has become the most advanced technology to date.

1)    Very helpful for Humans

Artificial Intelligence is really efficient in reducing our efforts in a number of areas. The applications that are equipped with AI Technology can do the work in a much faster way and with the best results. AI machines complete their work without any error and in a very efficient manner. Nowadays many sectors have started using AI technology and reduced the human efforts to an optimum level along with providing faster and efficient results.

2)    Used in Medical Science

Artificial Intelligence has changed the medical world completely!  There are endless areas of medical science where AI is regularly used to get valuable work from it. Nowadays, a virtual health care guide can be created that is used for analysis and research purposes. These are widely used to offer continuous health support to patients. These bots can easily answer your questions and schedule the appointments in a quick time.

3)    Used in Air Transport

Artificial Intelligence has a noticeable presence in Air transport. There is a wide array of functions in the management process & machines that are regularly controlled by artificial intelligence. Right from booking tickets to takeoff as well as the operation of the flights is duly taken care of through AI.

Benefits of AI

Artificial Intelligence is all about the complicated amalgamation of mathematics, computer science, and other complex sciences. Complex programming lets these machines mimic our cognitive abilities.

Some of the benefits of AI are as follows: -

  • Error Reduction

Artificial intelligence can help in lessening the error to an extreme level and to reach the probability of accuracy with great precision. It is applied effectively in a number of studies such as in space exploration.

Intelligent robots can be created with the help of this technology and they can be sent to space to explore it. As they are mere machines made of metal, they are much more resistant and possess great ability to withstand the hostile atmosphere of the space.

  • Daily Application

Application of Artificial Intelligence can be commonly seen in our daily lives. Siri or Cortana applications are the best examples of this.

The GPS we use in our day to day life is also based on AI. How surprising it is that we are using AI daily without even noticing this technology. When we type, it can predict what we are likely to type and it corrects our spelling. This is the best example of machine intelligence.

The application of AI can also be seen when we are taking a picture and AI technology detect the face of the person and also tags the people the time we are about to post our photos on the social media sites.

AI is widely used by banking and financial institutions for organizing as well as managing the data. Fraud detection in smart card systems too uses AI which is very helpful for our security.

  • Difficult Exploration

Artificial Intelligence, as well as the robotic science, can be used in mining as well as in another kind of fuel exploration procedures. Not only this, these machines are used in the exploration of the ocean floor thereby helping the humans to overcome the limitations.

As robots work due to their programming, they can easily perform more complex tasks with much ease & greater responsibility. Besides, they also don’t get exhausted.

  • Repetitive Jobs

Artificial Intelligence is a way better than humans as it can do repetitive jobs without any boredom. As machines are faster than humans so they can easily work as multitaskers. Artificial intelligence techniques can be used to carry out very dangerous tasks. We can adjust their parameter easily as their time and speed are merely parameters that are calculation based.

When we play a game or try to use a robot that is computer-controlled, we are actually communicating with artificial intelligence. In the game, the machine intelligence plans the movement of the game in response to the movements of the human players. So, gaming can be said as one of the most common usages of artificial intelligence.

  • Digital Assistants

A large number of big organizations are using digital assistants who can interact with the users just like human thereby saving any need for human involvement.

Humans are emotional and can take wrong decisions, but robots made up with artificial intelligence can’t be wrong as they do not have any emotions. So, they can think logically and take the right decisions that are already programmed.

Medical Applications

We are also a witness to artificial intelligence used in the Medical Field. There are numerous usages of AI in the medical field. Doctors can diagnose the patients as well as any risk related to their health through artificial intelligence. It also provides information to them about any kind of side effects of a range of medicines.

Today, medical professionals are properly trained with the surgery simulators that are run by Artificial Intelligence. These simulators are very useful in monitoring and detecting neurological disorders as they can easily simulate the functions of the brain.

Nowadays, robotics are often used in resolving the problems of the patients who are suffering from any mental disease such as depression etc. Artificial intelligence can be used in radiosurgery that is used in tumor operations and it can help the doctors to treat the tumor without even destroying the tissues that are surrounding it.

Disadvantages of AI

  • High Cost
  • This technology can’t be enhanced with experience
  • Loss of Creativity
  • Unable to replicate humans completely
  • Lead to Unemployment

Machine Learning

Machine learning is said to be an application of AI which offers the systems a power to learn & improve automatically. Machine learning paves the way for developing computer programs that can be used to access the data and learn things.

The learning process starts with the data observation like instruction methods, direct experience etc. so as to take better decisions in the time to come. The main aim of this learning is to help computers learn in an automatic manner without any intervention of humans & to adjust any kind of actions accordingly.

Machine learning can be considered as a subset of popular technology named AI that is focused on machine learning and can make predictions with its help.

Machine learning enables machines or computers to make decisions that are data-driven rather than being strategically programmed for a certain task.

These algorithms or programs are perfectly designed to learn as well as improve the time when we get new data.

Some of the methods of machine learning are as follows: -

  • Supervised machine learning algorithms
  • Semi-supervised machine learning algorithms
  • Reinforcement machine learning algorithms
  • unsupervised machine learning algorithms

Importance of machine learning

Machine Learning has gained prominence due to the inexpensive computational handling, information stockpiling, developing volumes of accessible information etc.

With the help of machine learning, intelligent models that are capable of dissecting information in a quicker way can be created. By doing this, big companies can stay away from any potential danger as that can be sensed at an early stage.

Some of the types of organizations that are using machine learning are as follows: -

1)    Administrations

Machine Learning is best utilized by banks and organizations that are related to the money industry. Machine learning is used to differentiate important experiences in information. The knowledge bits can help financial specialists to know the best time to exchange.

2)    Government Offices

Government offices too have started utilizing machine learning for their benefits. This technology can help recognize the misrepresentation & can also limit the data fraud.

3)    Human Services

Machine learning has started gaining prominence in the industry of human services through wearable sensors and gadgets that can leverage the vital information to judge the well being of the patient. This innovation can help restorative specialists to separate the information to recognize the warnings and patterns that might prompt enhanced treatment and conclusions.

Advantages of Machine Learning

Following are some of the advantages of machine learning: -

  • Simplifies product marketing
  • Forecasting of accurate sales
  • Accurate medical predictions
  • Easy Spam Detection
  • Recommendation for the right product

Disadvantages of Machine Learning

  • Error susceptibility
  • Time-taking
  • Automation

Deep Learning

Deep Learning is a set of algorithms that are employed in machine learning. Deep learning is used for modeling high-level data abstractions with the help of model architectures that are made of several nonlinear transformations. This is a small part of a big family that is in use for machine learning that is based on the data’s learning representations.

Deep learning is a technique of machine learning that let computers understand as to what humans feel in a natural way. You might have imagined knowing that deep learning technology is behind the driverless cars that let them identify the stop sign and to make them distinguish between a lamppost and a pedestrian. This key technology works behind consumer devices such as TVs, tablets, hands-free speakers and phones. Due to these impossible things, deep learning is getting noticeable attention in the world.

In Deep Learning Technology, a computer learns to do classification chores by using text, sound, and images. With deep learning, greater accuracy can be achieved.

Importance of Deep Learning

Deep learning is an immensely important technology that has made our lives smoother. With the help of deep learning, humans can let the machines to work for a number of tasks such as image recognition, procession, image recognition, computer vision, natural language processing etc. In a methodology called supervised learning methodology, the bulk of data is entered in the system so that the machine can recognize whether the output is wrong or right with the help of the labeled data.

In the unsupervised learning methodology, there is not any existence of labeling and the machine has to come to a particular decision itself whether the decision was wrong or right.

Learning methodology called semi-supervised learning methodology exists between unsupervised and supervised learning.

Applications of Deep Learning

Deep Learning Technology finds applications in numerous industries that are as following: -

  • Automated Driving
  • Medical Research
  • Electronics
  • Aerospace and Defense
  • Industrial Automation

Advantages of Deep Learning

  • Human-like learning
  • Helps in creating AI applications

Disadvantages of Deep Learning

  • Requires a large volume of data
  • No guidance on determining the topology

Data Science

Data Science can be considered as the study of the source of information, the representation of information and how it can be a valuable resource in creating a business as well as IT strategies. Mining high volumes of unstructured and structured data for the identification of patterns can help a firm increase its efficiencies, identify new market and increase the competitive advantage of the organization.

Data science field uses statistics, computer science disciplines and mathematics & absorb the techniques such as cluster analysis, data mining and machine learning.

Data science is an amalgamation of a number of algorithms, tools & machine learning principles to explore hidden patterns out of the raw data.

Data science impacts theoretical and applied research in a number of different fields such as machine translation, robotics, digital economy, businesses, health care, finance, social sciences, speech recognition, and search engines.

Importance of Data Science

In the past few years, the advent of Data Science has changed the technological concept to an extreme level. We have been much advanced and our lives have been made much easier and the credit goes to Data Science. Right from LinkedIn website to Tinder, this technology is applied nearly everywhere.

Apart from the technological applications of Data Science, there have been numerous business applications of this technology.

Data Science is gaining much prominence in adding value to a number of business models with the help of deep learning and statistics to provide better decisions and to improve hiring. Data Science is also used to predict the situations or risk so that we can sense them beforehand and avoid them completely. 

Applications of Data Science

Companies that are using Data Science are intelligent enough to sell products according to the interest and the purchasing power of the customers.

1)    Digital Advertisements

2)    Internet Search

3)    Image Recognition

4)    Speech Recognition

5)    Airline Route Planning

6)    Gaming

7)    Delivery Logistics

8)    Fraud & Risk Detection

Advantages of Data Science

  • Lessening the risk or fraud
  • Helps in delivering accurate products at an accurate time
  • Can lead to best customer experiences

Artificial Intelligence vs Machine Learning vs Deep learning vs Data science: An Analysis

Data Science

Data science consists of the Data Analysis. This can be said as a vital component of the skills that are required for a number of jobs in this field. However, this is not the only skill which is required. It plays an active role in the implementation and design of 4 related areas: -

  • In data acquisition
  • In data archiving
  • Data architecture
  • Data analysis

Machine Learning

There are 3 kinds of learning algorithms that are as follows: -

  • Supervised Machine Learning Algorithms

We employ this algorithm in order to make the predictions. Besides, this type of algorithm looks for the patterns in the value labels that is allocated to data points.

  • Unsupervised Machine Learning Algorithms

No any label is related to the data points. These algorithms arrange the data in clusters. Besides, it requires a description of the structure.

  • Reinforcement Machine Learning Algorithms

These algorithm types are used for choosing an action. Also, they can be used to judge as to whether they are based on each point of the data. Besides, the algorithm makes a change in its strategy to learn in a better way.

Deep Learning

Machine learning is focused on resolving the problems related to the real world. Also, this technology takes in some ideas of the technology called artificial intelligence. Besides, this technology acts with the help of neural networks which are designed for mimicking the capabilities of the decision making of humans.

Machine learning techniques and tools are focussed on the technology called deep learning. Also, we are required to apply it to solve any problem that needs a thought- whether it is human or artificial.

A deep neural network is comprised of 3 kinds of layers that are as follows: -

  • The hidden layer
  • The output layer
  • The input layer

Artificial Intelligence

Artificial Intelligence is actually a much broad term. It can be called as an attempt to let computers think just like human beings.

Artificial intelligence can be as easy as a child’s play. It really makes no difference as to how complex the system is, artificial intelligence technology is just in its nascent phase.

Relation of Data Science to Artificial Intelligence, Machine Learning, and Deep Learning

Data Science can be called inter-disciplinary field that can be applied in numerous fields such as machine learning, visualization, statistics etc. This is a general procedure which analyzes as well as manipulates the data. Also, it enables to find appropriate information and meaning out of huge volumes of data. This enables us to employ the data for making strong decisions in science, technology, politics, and business.

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