The Basics And Purpose of Machine Learning

The Basics And Purpose of Machine Learning

To understand the basics of machine learning it is important to know what it is. In the simplest terms, machine learning is the ability of a computer system or software platform to teach itself. It is a form of ‘self-programming’ that allows a software platform to come to its own decisions via datasets and outside information without the need for direct human programming. While it’s not a hard concept to understand (self-learning computers) the basics of how it works and how it can be useful requires more detail.

Machines Learning Versus Human Input

Machine learning allows a computer, software platform, system, etc. to actively react to new information. This means that when a novel situation or dataset presents itself the machine will modify its process to fit this new information which in turn modifies its results. The existing method of software and system development creates software that cannot ‘think’ of its own results responses and is limited to a set series of possible responses coded into the software by its programmers.

While this has been the common method of software created for the entire lifespan of computers the datasets and information software is required to read has become very complex. Programming ways to interpret such vast amounts of information has become difficult for even the best programmers to conceptualize. This is why machine learning is so important. It allows for the creation of methodologies beyond human planning and foresight.

Why This Is Useful

The chief advantage of machine learning is that it takes pressure off of software developers. Under our existing paradigm software and computer systems only know what a programmer tells them to know. This means that a software system cannot innovate and all that it can do must be thought of by the persons who programmed it. With machine learning, a system is no longer limited by the programmers very human vision and can learn its own methods and reach goals through new and innovative processes.

This is very useful because it allows programmers to create software with a specific goal in mind and a purpose it is meant to achieve without having to focus on the entire process of how it does so. Machines have a much wider scope of data processing ability than humans possess and can organize and scan data for important information far more quickly than any person ever could. Machine learning allows software to be goal oriented and also allows for machine developed processes that programmers may not have even considered. It not only creates more useful software but also more effective software.

Machine learning has potential uses in search engines, finance, medical diagnosis, retail environments, e-commerce, space travel, debugging and robot technologies to name just a few. Machine learning processes, algorithms, and different strategic approaches for machine learning will be covered in future blogs.

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