Machine Learning Is a Crucial Aspect to Technological Expansion

The concept of artificial intelligence is something that has fascinated mankind for a long time. With the advancements that have been made in technology, the world is finally approaching a place where it may finally experience true artificial intelligence. Machine learning is a specific application of artificial intelligence. 

It’s likely that you have heard much about machine learning and how it’s affecting the future of business. There’s a lot of potential in the field. Machine learning is going to affect how people do business and live their lives. It should be mentioned that machine learning isn’t true artificial intelligence. It merely uses many of the concepts and ideas behind artificial intelligence to grow as a program. 

What Exactly is Machine Learning? 

As mentioned, machine learning is an application of artificial intelligence. Specifically machine learning talks about computer programs which absorb data and then learn and improve from the data. The idea is that the program evolves from the data, rather than the explicit code of the programming behind the scenes. 

A lot of machine learning involves pattern recognition and observations. Data is observed, patterns recognized, which in turn will cause the software to make a different decision. Imagine machine learning examining the data of stock transactions until it identifies a pattern. From there, the machine will automatically purchase or sell stocks in relation to what it has identified without needing to be told to by the program itself. 

An interesting aspect of machine learning is that it doesn’t read text as text. Instead, it reads it as a series of keywords. By doing this, it can better understand the actual text through semantic analysis. 

Types of Machine Learning

There’s four main types of algorithms that are used with machine learning. They include: 

• Supervised machine learning algorithm - A supervised algorithm takes in a large amount of past data. Specifically the data of the past has been labeled by the users to show examples of events. From there, the algorithm will attempt to predict future events. As it makes predictions on outcomes, it will compare the actual outcome to the prediction and can further revise from this information. 
• Unsupervised machine learning algorithm - With these algorithms, there’s simply no classification or labels on the data that is used beforehand. This is better at understanding and learning a function within the hidden structures of the data. It doesn’t make predictions, but looks for hidden structures. 
• Semi-supervised machine learning algorithm - These machine learning algorithms are a sort of hybrid of the previous two. In most cases there’s a smaller amount of labeled data and a large amount that is unlabeled. This can allow the algorithm to learn much more efficiently. 
• Reinforcement machine learning algorithm - This is a very different type of machine learning and can be boiled down to a “trial and error” system. It produces actions and then either is rewarded or shown an error. This type of machine learning is ideal for software trying to learn specific ideal behaviors. 

How Will Machine Learning Benefit Business? 

The biggest benefit of machine learning comes with how companies handle data. Big data is arguably one of the largest opportunities for growth in business today. Machine learning specially is always examining data in real time and can help interpret and allow for fast decisions to be made. Any business using machine learning to help with their decision making can find themselves ahead of their competition. 

Another benefit to machine learning is the ability to eliminate a lot of the manual tasks that are completed each day by employees. Repetitive tasks have been a part of jobs for as long as there have been jobs. But machine learning often is able to eliminate many of them through the predictive models it creates. 

Machine learning is also a big part of network security. The way it analyzes data can be applied to network activity. This means that possible intrusions are recognized immediately and actions can be taken against the offending hackers.