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   Krishna Vijayan

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   Krishna Vijayan

   2021-10-22T21:59:52+05:30Added an answer on October 22, 2021 at 9:59 pm

   Artificial Intelligence, Machine Learning, Deep Learning And Data Science are some of the words that you come through internet frequently, specially, if you’re learning about computer. If these terms, Artificial Intelligence, Machine Learning, Deep Learning, Data Science confuses you in anyway, I’ll drop below the explanations about what they are and what are the main differences between each of them.

   Artificial Intelligence:

   Artificial intelligence is a field of computer science which makes a computer system that can mimic human intelligence. It is comprised of two words “Artificial” and “Intelligence”, which means “a human-made thinking power.” Hence we can define it as, Artificial intelligence is a technology using which we can create intelligent systems that can simulate human intelligence.

   Machine Learning: 

   Machine learning is about extracting knowledge from the data. It can be defined as, Machine learning is a subfield of artificial intelligence, which enables machines to learn from past data or experiences without being explicitly programmed. Machine learning enables a computer system to make predictions or take some decisions using historical data without being explicitly programmed. Machine learning uses a massive amount of structured and semi-structured data so that a machine learning model can generate accurate result or give predictions based on that data.

   Deep Learning: 

   Deep learning is a subset of machine learning, which is essentially a neural network with three or more layers. These neural networks attempt to simulate the behavior of the human brain—albeit far from matching its ability—allowing it to “learn” from large amounts of data. While a neural network with a single layer can still make approximate predictions, additional hidden layers can help to optimize and refine for accuracy.

   Data Science: 

   Data science combines the scientific method, math and statistics, specialized programming, advanced analytics, AI, and even storytelling to uncover and explain the business insights buried in data. Data science is a multidisciplinary approach to extracting actionable insights from the large and ever-increasing volumes of data collected and created by today’s organizations. Data science encompasses preparing data for analysis and processing, performing advanced data analysis, and presenting the results to reveal patterns and enable stakeholders to draw informed conclusions.

    

   Main Differences Between Artificial Intelligence, Machine Learning, Deep Learning And Data Science:

   • Data science can be seen as an umbrella for all the disciplines used to make sense out of huge volumes of data. Data science research is the foundation for building smart AI products whether they are ML-based or DL-based.
   • Unlike data science, data mining is referred to as a set of techniques and tools used for collecting, cleansing, and analyzing data to unfold interesting patterns and trends in it. Data mining is also commonly used when working on AI projects.
   • AI is about creating a functional data product that can solve set tasks by itself, which remotely resembles human problem-solving.
   • Machine learning falls within an AI system that can self-learn based on algorithms and previously learned patterns.
   • Deep learning is a kind of machine learning but this approach uses neural networks for making predictions based on processed data.
   • Most AI work involves either ML or DL since the so-called “intelligent” behavior of machines requires massive knowledge, which, in turn, requires data science and data mining research.

   Hope this answer helped. Also read, How did Artificial Intelligence changed the world?

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