The Buzzword - What is Machine Learning?
What exactly is Machine Learning
, one of the hottest topics in the today's IT industry?
Simply put, machine learning is a technology that enables computers to learn and make decisions autonomously based on data.
While traditional programming involved computers following fixed rules defined by developers, machine learning allows computers to discover
rules
andpatterns
within data to solve problems.
For instance, an email spam filter learns from a a large number of emails, identifying specific patterns to differentiate between spam and legitimate emails.
AI powered by machine learning can process massive datasets and solve problems at incredible speed.
While it would be impossible for a human to read and classify thousands of emails in a single day, an AI model trained through machine learning can complete the task in seconds.
The History of Machine Learning
The origins of machine learning date back to the late 1950s and early 1960s.
In the early 1950s, computer scientist Alan Turing
first proposed the possibility of computers thinking like humans.
In 1956, the first academic conference on Artificial Intelligence (AI) took place in Dartmouth, USA, marking the birth of the term and concept of Artificial Intelligence (AI)
.
By 1959, Arthur Samuel had coined the term Machine Learning
, demonstrating that computers could improve their performance through learning without explicit programming.
This milestone established machine learning as a critical branch of AI, and ongoing research has since made it an essential part of various technical fields.
How is Machine Learning Applied?
Technologies we encounter daily, such as facial recognition, chatbots, recommendation systems, and speech recognition, are predominantly based on machine learning.
Machine learning identifies patterns in massive datasets to make predictions and decisions. It has evolved to include artificial neural networks, which mimic the structure of the human brain, and deep learning, a more advanced technique built upon them.
In the next lesson, we’ll take a closer look at artificial neural networks.
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