The 1950s was the decade in which technological innovations resulted in the rapid improvement of mass communication. It is at the end of this decade that television had replaced radio, newspapers and magazines as the primary source of information and entertainment for most Americans. In 1959, the term ‘machine learning’ was coined by Arthur Samuel who was a pioneer in the field of computer gaming and artificial intelligence (AI).
Machine learning is not a new concept but has gained a lot of momentum in recent years through the expanding collection of data, affordable processing power and inexpensive storage. A machine learning course, as an area of AI and computer science, promises a smarter connection between humans and computer systems through intelligent interactions.
Topics such as the development of software and algorithms that can make predictions based on data are covered in this course. Machine learning further enables computer systems to make predictions or decisions using historical data or experiences without being explicitly programmed. It is a powerful tool that can be applied to almost any problem, such as, theoretically, smarter non-player characteristics (NPC) in computer games.
These characters in a game are not controlled by any person playing, nor by any form of AI, and they are usually not meant to act like real people. NPC are different from central processing unit (CPU) characters, which are built to act like humans in games, but that’s a topic for another day.
Machine learning makes predictions by constructing algorithms that look for and recognise patterns in data through previously collected data. Implementations of these algorithms are trained on a set of training data, allowing them to improve themselves. The training data is the same kind of data that is to be supplied to the running program, along with the desired result. The program then assesses its own performance and adjusts to improve.
A speech recognition device is an ideal example of devices that learn by recognising patterns in data. It converts audio from a speech recording into a single sound and finds the most probable word in a specific language through the use of algorithms. Those sounds are then translated into text, enhancing human communication for people with hearing issues.
If more people were to study this machine learning course, as a human race, we would stand a chance to benefit greatly in various sectors, including the social and health sectors. We could expect an acceleration in technological advancement from the effective use of machine learning.
