Ai and deep learning in data science

Both AI and Deep Learning are naturally connected with Data Science and have very similar objectives. It is known that their applicability has already been proved to be interlinked. Some Applications of data science, deep learning, and artificial intelligence are discussed in the review below.

AI (Artificial Intelligence)The vast dimensions of the human mind, the vaulting intelligence and creative urge, still overshadows the machine by far. But in certain aspects, the progress of AI is astonishing. Decision-making, speech recognition, language translation and visual perception, are all tasks that the computer is beginning to perform with superb acuity. But while human beings can use whatever data is available at any given point of time to make rapid decisions, Artificial intelligence (AI) needs massive chunks of data to duplicate even a small percentage of that ability, and clear the simplest objectives.

Data ScienceThe term "Data Science" encompasses much more than machine learning. Instead, It covers the whole spectrum of data processing. It combines mathematics and statistics, AI and machine learning, and dedicated programming, with powerful tools, to be able to extract knowledge from Big Data, convert it into insights, and finally obtain and communicate benefits to the stakeholders of the business.

Deep Learning

Human Beings understand situations and make decisions based on that learning naturally. But computer systems find this jump quite difficult, and need special processes to arrive at a decision. The process of learning from Data over time is what drives Machine Learning, and its subset Deep Learning. At the same time, Deep Learning strengthens the process of AI and Data Science by teaching computer systems the art of interpreting Data, to come to a definite decision. Unlike Humans, computer systems need a lot of learning, involving massive quantities of data and implementation to achieve the kind of insights that we achieve seemingly without effort. It is Deep Learning that is creating Voice Pattern Recognition and control and even driverless cars that we are gradually beginning to take for granted.

General ApplicationsSome of the technologies and services that use all three are as follows:

Google: The Google search engine uses algorithms created by Machine Learning and Deep Learning to search and locate multiple Data regarding the search queries of Users. In a matter of microseconds, Google combs through more than a Billion pages to rank the best possible answers for the User.

Speech Recognition: Exhaustive Machine Learning, working through AI neural networks, enforces Speech Recognition by smart phones, to help the User with answers to practical queries without typing a single word.

Expert Systems: IBMs Watson computer system can collect, absorb and process Data much faster than humans, with an unbelievable accuracy of 90%, because of its AI-driven Deep Learning.

Robotics: independent processors within mobile or static robots can carry out tasks automatically and continuously through Data implementation by AI and Deep Learning.

These are only some of the Applications of data science deep learning ai artificial intelligence, amongst many others.

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