Machine learning is a method of data analytics, which automates analytical model building. The main idea of machine learning is to build systems, which can identify patterns, learn from data and make predictions and decisions with minimal or no human intervention. With the new and more advanced computing technologies, machine learning these days is nothing like machine learning in its infancy.
Before machine learning techniques, pattern recognition influenced machine learning. Machine learning was also born from the theory stating that machines and computers can learn from any kind of data just from experience without any need for humans to program them to perform miscellaneous tasks. Therefore, researchers involved in AI began testing to see if machines could really learn to identify different patterns on their own from any kind of data.
The main iterative aspect of machine learning techniques is important as machine learning models get exposed to new data, so they can adapt easily and independently. Machine learning models learn from previous computations to produce repeatable as well as reliable results and decisions. Machine learning is not a new science, but it has gained fresh momentum followed by the latest technology advancements.
Despite the fact many machine learning techniques and many machine learning algorithms have been around for a while, their ability to automatically apply complex mathematical calculations on big data in a reputable manner and to be able to do it so rapidly is a very recent development. This recent machine learning techniques development enabled modern machine learning applications such as self-driving cars, online recommendation systems like those you see on Netflix, Amazon and every other search engine.
Machine learning techniques are also commonly combined with the main linguistic rule creation. Machine learning is also used for fraud detection, spam filtering and many other important uses in the modern world.
The topic for discussion of our next post will be, how machines learn on their own.