[.NET, Angular, DevOps, Искусственный интеллект, Data Engineering] Data Science vs AI: All You Need To Know
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What do these terms mean? And what is the difference?
Data Science and Artificial Intelligence are creating a lot of buzzes these days. But what do these terms mean? And what is the difference between them?
While the terms Data Science and Artificial Intelligence (AI) comes under the same domain and are inter-connected to each other, they have their specific applications and meaning.
There’s no slowing down the spread of AI and data science. Many big tech giants are extensively investing in these technologies. As per the recent survey, it is estimated that artificial intelligence could add $15.7 trillion to the global economy by 2030.
Through this piece of writing, I will be explaining about the AI and data science concepts and their differences in detail. So, without wasting any more time, let’s get started!
What Exactly is Data Science?
Data science is an idea of bringing together information investigation and their associated strategies to understand the real wonders with data.
The need for data processing has increased significantly for industries after the explosion of large-scale data collected by them through various mediums of the Internet, such as laptops, smartphones, desktops, etc.
According to a Gartner report, 75% of the 10 million registered organizations in India are planning to invest in data science and machine learning.
Companies are now reliant on data to make any decisions related to almost everything about the organization. These decisions are used for better services and products, modifications, eliminating and adding various things, etc.
And all this is possible only if you have a sufficient amount of data so that different algorithms can be applied to that data so that you get more accurate results.
Data science has thus revolutionized almost all industries. Modern societies are all data-driven, and this is why data science has become an essential part of the contemporary world.
Data science involves data extraction, manipulation, visualization, and maintenance of data to predict the occurrence of future events at various stages and processes.
Artificial Intelligence: A brief introduction
AI is just a computer capable of mimicking or imitating human thought or behavior. Within that, there is a subset known as machine learning that is now cultivating the most exciting part of AI.
By allowing computers to learn to solve problems on their own, machine learning has created a series of successes that once seemed almost impossible.
In other words, AI can be defined as a collection of mathematical algorithms that make computers understand the relationships between different types and segments of data and to use this knowledge of connections to come to conclusions or make decisions. That can be accurate to a much higher degree.
In short Artificial Intelligence has the universal field of “intelligent-seeming algorithms”, with machine learning currently being the leading frontier.
According to a survey conducted by Intel, it is predicted that 70% of Indian companies will deploy AI-enabled solutions by the end of 2020.
As you can see that there is a huge demand for AI, so it will be a great idea to contact machine learning companies in India if you want to integrate this technology.
Data Science Vs AI: What’s the difference?
Although the terms Data Science and Artificial Intelligence can be related and interconnected, each of them is unique in its way and used for different purposes. Data science is a broad term, and machine learning falls within it.
Let us discuss some significant differences between AI and data science:
Scope:
Artificial intelligence is limited only to the implementation of the ML algorithm, while data science involves various underlying operations of data.
Type of Data:
Artificial intelligence consists of standardized data in the form of vectors and embedding, but, on the other hand, data science will contain many different types of data such as structured, semi-structured, and unstructured data.
Utilities:
The utilities used in Artificial Intelligence are Mahout, Shogun, TensorFlow, PyTorch, Kaffe, Scikit-learn, and tools used in data science include Keras, SPSS, SAS, Python, R, etc.
Applications:
Artificial intelligence applications are used in many fields such as the healthcare industry, transportation industry, robotics industry, automation industry, and manufacturing industries.
Data science applications are actively used in the field of search engines such as Google, Yahoo, Bing, including the Marketing sector, Banking, Advertising field, and many others.
Process:
In the process of artificial intelligence, predictions are made using predictive models. On the other hand, data science involves the operation of prediction, visualization, analysis, and data pre-processing.
Techniques:
Artificial intelligence will use algorithms in computers to solve the problem, while data science involves many different methods of statistics.
Purpose:
The primary objective of Artificial Intelligence is to automate the process and bring autonomy to the data model. But the primary goal of data science is to find patterns that are hidden in the data. They both have their aims and objectives which are different from each other.
Different Models:
In Artificial Intelligence, models are created that are expected to resemble human comprehension and cognition. In data science, models are constructed to produce insights that are statistical for decision making.
Degree of Scientific Processing:
Artificial intelligence will use a much higher level of scientific processing than data science which uses less scientific processing.
Bottom Lines
In this data science vs AI blog, we came to know that the two terms are used interchangeably. Artificial intelligence is yet to be discovered, but on the other hand, data science has already started making a significant change in the market. Data science converts data, which can be used for visualization and analysis.
With the help of Artificial Intelligence, new products are created that are better than before, and it also brings autonomy by doing many things automatically. With the help of data science, data is analyzed, based on which careful business decisions are made that provide many benefits to companies.
If you want to implement these technologies into your services, then you must hire AI developers in India. They offer various AI learning solutions to businesses.
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Источник:
habr.com
===========
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What do these terms mean? And what is the difference?  Data Science and Artificial Intelligence are creating a lot of buzzes these days. But what do these terms mean? And what is the difference between them? While the terms Data Science and Artificial Intelligence (AI) comes under the same domain and are inter-connected to each other, they have their specific applications and meaning. There’s no slowing down the spread of AI and data science. Many big tech giants are extensively investing in these technologies. As per the recent survey, it is estimated that artificial intelligence could add $15.7 trillion to the global economy by 2030. Through this piece of writing, I will be explaining about the AI and data science concepts and their differences in detail. So, without wasting any more time, let’s get started! What Exactly is Data Science? Data science is an idea of bringing together information investigation and their associated strategies to understand the real wonders with data. The need for data processing has increased significantly for industries after the explosion of large-scale data collected by them through various mediums of the Internet, such as laptops, smartphones, desktops, etc. According to a Gartner report, 75% of the 10 million registered organizations in India are planning to invest in data science and machine learning. Companies are now reliant on data to make any decisions related to almost everything about the organization. These decisions are used for better services and products, modifications, eliminating and adding various things, etc. And all this is possible only if you have a sufficient amount of data so that different algorithms can be applied to that data so that you get more accurate results. Data science has thus revolutionized almost all industries. Modern societies are all data-driven, and this is why data science has become an essential part of the contemporary world. Data science involves data extraction, manipulation, visualization, and maintenance of data to predict the occurrence of future events at various stages and processes. Artificial Intelligence: A brief introduction  AI is just a computer capable of mimicking or imitating human thought or behavior. Within that, there is a subset known as machine learning that is now cultivating the most exciting part of AI. By allowing computers to learn to solve problems on their own, machine learning has created a series of successes that once seemed almost impossible. In other words, AI can be defined as a collection of mathematical algorithms that make computers understand the relationships between different types and segments of data and to use this knowledge of connections to come to conclusions or make decisions. That can be accurate to a much higher degree. In short Artificial Intelligence has the universal field of “intelligent-seeming algorithms”, with machine learning currently being the leading frontier. According to a survey conducted by Intel, it is predicted that 70% of Indian companies will deploy AI-enabled solutions by the end of 2020. As you can see that there is a huge demand for AI, so it will be a great idea to contact machine learning companies in India if you want to integrate this technology. Data Science Vs AI: What’s the difference?  Although the terms Data Science and Artificial Intelligence can be related and interconnected, each of them is unique in its way and used for different purposes. Data science is a broad term, and machine learning falls within it. Let us discuss some significant differences between AI and data science: Scope: Artificial intelligence is limited only to the implementation of the ML algorithm, while data science involves various underlying operations of data. Type of Data: Artificial intelligence consists of standardized data in the form of vectors and embedding, but, on the other hand, data science will contain many different types of data such as structured, semi-structured, and unstructured data. Utilities: The utilities used in Artificial Intelligence are Mahout, Shogun, TensorFlow, PyTorch, Kaffe, Scikit-learn, and tools used in data science include Keras, SPSS, SAS, Python, R, etc. Applications: Artificial intelligence applications are used in many fields such as the healthcare industry, transportation industry, robotics industry, automation industry, and manufacturing industries. Data science applications are actively used in the field of search engines such as Google, Yahoo, Bing, including the Marketing sector, Banking, Advertising field, and many others. Process: In the process of artificial intelligence, predictions are made using predictive models. On the other hand, data science involves the operation of prediction, visualization, analysis, and data pre-processing. Techniques: Artificial intelligence will use algorithms in computers to solve the problem, while data science involves many different methods of statistics. Purpose: The primary objective of Artificial Intelligence is to automate the process and bring autonomy to the data model. But the primary goal of data science is to find patterns that are hidden in the data. They both have their aims and objectives which are different from each other. Different Models: In Artificial Intelligence, models are created that are expected to resemble human comprehension and cognition. In data science, models are constructed to produce insights that are statistical for decision making. Degree of Scientific Processing: Artificial intelligence will use a much higher level of scientific processing than data science which uses less scientific processing. Bottom Lines In this data science vs AI blog, we came to know that the two terms are used interchangeably. Artificial intelligence is yet to be discovered, but on the other hand, data science has already started making a significant change in the market. Data science converts data, which can be used for visualization and analysis. With the help of Artificial Intelligence, new products are created that are better than before, and it also brings autonomy by doing many things automatically. With the help of data science, data is analyzed, based on which careful business decisions are made that provide many benefits to companies. If you want to implement these technologies into your services, then you must hire AI developers in India. They offer various AI learning solutions to businesses. =========== Источник: habr.com =========== Похожие новости:
Искусственный интеллект ), #_data_engineering |
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Текущее время: 25-Ноя 21:45
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