What Are History Of Machine Learning?
Machine learning is part of artificial intelligence, where computer algorithms are initially used to learn from data and information. Machine learning computers do not require to be programmed and can change and improve their algorithms by themselves.
Machine learning algorithms currently help computers communicate with humans, autonomously drive cars, write and publish sport match reports, and find suspects. Machine learning severely impacts most industries and the jobs revolving around them. Which is one of the reasons considering Machine Learning Bootcamp is a wise idea for IT candidates.
Let us see how machine learning originated and covered various milestones over the years.
In 1950, Alan Turing created the “Turing Test” for determining if a computer has real intelligence. For passing the test, a computer had to fool a human into believing it is also human. In 1952 Arthur Samuel wrote the first computer learning program. The computer played with a game of checkers and improved the game as it played; studying the game made some winning moves and strategies and incorporated these moves into its program. 1957 Frank Rosenblatt designed the neural networks for computers or the Perceptron that simulated the thought processes of the human brain. A decade later, in 1967 algorithm was written, which allowed computers to begin using fundamental pattern recognition. Later in 1981, Gerald Dejong introduced the concept of Explanation Based Learning (EBL), in which a computer analyzed training data and created a general rule it could follow by discarding unimportant data.
By the 1990s, machine learning shifted from a knowledge-driven approach to a data-driven approach. Scientists started creating programs for computers for analyzing large amounts of data and learn from it. 2006 Geoffrey Hinton coined the term “Deep Learning” to explain new algorithms that could aid computers in observing and distinguishing objects and text in images and videos. In 2015 Amazon launched its machine learning platform and Microsoft in the same year created distributed machine learning toolkit that enabled the efficient distribution of machine learning problems across multiple computers.
Also, over 3000 AI and Robotics researchers, endorsed by Stephen Hawking, Elon Musk, and Steve Wozniak, signed an open letter warning of the danger of autonomous weapons which choose and connect targets without human intervention. In the following year, Google’s AI algorithm beat a professional player at the Chinese board game Go, which is considered very difficult and more complex than chess. So while there are many advantages to AI, some scientists believe that computers might never think the same way humans do. So comparing computational analysis and algorithms of the computer to machinations of the human mind is vague. While it is true that the computer’s ability to perceive and interact with the surroundings is growing at a high rate, simultaneously is the quantity of data produced by humans. So the demand for learning machine learning is vast and considered to have a greater reach in the times to come. Considering Machine Learning Training is a great way to begin a journey into an advanced and productive future. SynergisticIT is a leading name in Machine Learning Bootcamp with a dynamic curriculum and industry expert mentorship to provide you an edge over the competition. Contact today!
Machine learning algorithms currently help computers communicate with humans, autonomously drive cars, write and publish sport match reports, and find suspects. Machine learning severely impacts most industries and the jobs revolving around them. Which is one of the reasons considering Machine Learning Bootcamp is a wise idea for IT candidates.
Let us see how machine learning originated and covered various milestones over the years.
In 1950, Alan Turing created the “Turing Test” for determining if a computer has real intelligence. For passing the test, a computer had to fool a human into believing it is also human. In 1952 Arthur Samuel wrote the first computer learning program. The computer played with a game of checkers and improved the game as it played; studying the game made some winning moves and strategies and incorporated these moves into its program. 1957 Frank Rosenblatt designed the neural networks for computers or the Perceptron that simulated the thought processes of the human brain. A decade later, in 1967 algorithm was written, which allowed computers to begin using fundamental pattern recognition. Later in 1981, Gerald Dejong introduced the concept of Explanation Based Learning (EBL), in which a computer analyzed training data and created a general rule it could follow by discarding unimportant data.
By the 1990s, machine learning shifted from a knowledge-driven approach to a data-driven approach. Scientists started creating programs for computers for analyzing large amounts of data and learn from it. 2006 Geoffrey Hinton coined the term “Deep Learning” to explain new algorithms that could aid computers in observing and distinguishing objects and text in images and videos. In 2015 Amazon launched its machine learning platform and Microsoft in the same year created distributed machine learning toolkit that enabled the efficient distribution of machine learning problems across multiple computers.
Also, over 3000 AI and Robotics researchers, endorsed by Stephen Hawking, Elon Musk, and Steve Wozniak, signed an open letter warning of the danger of autonomous weapons which choose and connect targets without human intervention. In the following year, Google’s AI algorithm beat a professional player at the Chinese board game Go, which is considered very difficult and more complex than chess. So while there are many advantages to AI, some scientists believe that computers might never think the same way humans do. So comparing computational analysis and algorithms of the computer to machinations of the human mind is vague. While it is true that the computer’s ability to perceive and interact with the surroundings is growing at a high rate, simultaneously is the quantity of data produced by humans. So the demand for learning machine learning is vast and considered to have a greater reach in the times to come. Considering Machine Learning Training is a great way to begin a journey into an advanced and productive future. SynergisticIT is a leading name in Machine Learning Bootcamp with a dynamic curriculum and industry expert mentorship to provide you an edge over the competition. Contact today!
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