Buzz about machine learning and artificial intelligence seems to dominate the tech industry nowadays. For firms looking for an edge with big data and business intelligence, machine learning is the new frontier. But what exactly is it?
At its core, machine learning is a method of artificial intelligence, and it allows for a software agent to learn and improve on its own without outside development. Generally speaking, a large amount of data is given to the system as examples: a dataset. The software then analyzes the data and discovers hidden patterns and then learns from these patterns to be able to determine other possible applications.
Simply put, it’s a way for software to learn on its own.
Methods for Machine Learning
There are a few different methods that are used in machine learning. The most common is supervised machine learning. In this method, the software is provided with a dataset that’s been parsed, labeled or organized. Using the parameters provided, the software agent is able to learn and eventually make its own predictions based on the original dataset. The more accurate the data is that’s provided, the more accurate the predictions.
On the other end of the spectrum is unsupervised machine learning. This method is used to study raw, unprocessed data and how to discern patterns from it. These algorithms explore the datasets to draw inferences and find hidden patterns in the data that can then be used to make more intelligent decisions.
Both the unsupervised and supervised methods can be combined into a semi-unsupervised method. It usually involves a small but accurate dataset that the software agent can learn from. This learning is then applied to a much larger, uncategorized dataset. This can vastly improve the learning accuracy when applied to the larger dataset.
How it Can Help Your Business
When applied to business, machine learning can enhance and improve all aspects of operations, from finance to production to research and development. For any process or operation that deals with massive amounts of data, machine learning can be used to infer patterns and help businesses make more intelligent decisions.
One of the most popular ways of utilizing machine learning is through image recognition. Machine learning can be used to analyze large quantities of images and other high-resolution data to find patterns. It can be used in:
Machine learning can improve preventative maintenance in manufacturing businesses by parsing the large amounts of data that are available. It can discover patterns in the data and make intelligent decisions to aid in making optimal maintenance practices to prevent unnecessary failures and expenses. This practice—the successor to preventative maintenance—is known as predictive maintenance.
Machine learning is already being successfully applied to algorithmic trading, fraud detection and portfolio management. Large amounts of data and accurate historical data can give firms with machine learning an edge over competitors and help them make more accurate predictions.
Most e-commerce sites today use some form of machine learning for making product recommendations. The algorithms evaluate large amounts of customer purchase history and, cross-referencing it, can identify patterns in purchases, allowing it to group products together in ways that wouldn’t have normally been anticipated.
Machine learning and artificial intelligence take a considerable amount of resources and time to be trained correctly, but the benefits can’t be overstated. As technology moves forward, it’s going to become critical for businesses to look at the large amounts of data they have in fresh new ways. Machine learning can deliver accurate results and hidden patterns that equate to capitalizing on profitable opportunities or avoiding costly risks.