Artificial intelligence began with an idea — the thought that machines could mimic human intelligence with the right programming and skill. Machine learning translates that idea into action.
What is machine learning? And, how is it impacting the world? Here’s what you should know about machine learning and why it’s become a vital component for many major companies.
What is Machine Learning?
Machine learning is a form of artificial intelligence where machines learn to develop models by processing a large amount of data. These models determine outcomes or recognize patterns and create more accurate results over time.
Machine learning is an important step in creating artificial intelligence. Instead of creating a machine that produces certain results, the machine can make predictions on its own.
Though machine learning is a subset of artificial intelligence, data scientists are still involved in the training process. Depending on the approach used, data scientists may be more involved or less involved in training the machine.
There are two main approaches to machine learning: supervised learning and unsupervised learning. In supervised learning, data scientists label training data and have some control over the process. Meanwhile, with unsupervised learning, the data is not labeled, so machines have to recognize patterns and come up with results completely on their own.
What is a Machine Learning Model and How is it Built?
Machine learning models allow for machines to recognize a specific pattern in data. A machine needs to be trained before it can recognize a pattern.
Data scientists will often perform a series of steps to properly train machines. First, they have to make sure to set certain parameters and organize the data to make sure that the machine can work with the right objectives in mind. Depending on the approach used, the data may be labeled or not.
Once this step is complete, data scientists will begin building the machine learning model. Software like TensorFlow may be used to build the machine model. Data scientists will select an algorithm to run the data through it. As the results become more accurate, the model will continue to be developed until it meets a certain level of accuracy that is deemed adequate.
How Companies are Using Machine Learning
Many companies are using machine learning to solve problems and make everyday life easier. It has become a vital tool for research and progressed technology in innovative ways. Here are a few industries that machine learning has greatly impacted in the last few years.
As expected, many major technology companies utilize machine learning to enhance entertainment and communication. Whether it’s improving filters on one’s social media feed, or incorporating voice activation features into phones or home devices, machine learning is constantly finding ways to revolutionize the tech products that consumers use daily.
For example, Twitters’ timelines are curated by machine learning technology. The algorithms used essentially put a ranking on tweets and improves performance over time.
Apple also incorporates AI and machine learning into its products — fellow friend Siri is the perfect example. Since it was first implemented, Siri has improved its speaker recognition by learning to recognize patterns and behaviors.
Customer service is meant to make services and purchases easy and enjoyable. Major retail companies are using machine learning to analyze customer behavior and improve online customer experiences.
For instance, Nordstrom has recently pushed for a greater digital focus. According to an article from Forbes, Nordstrom is improving the personalization of its website through AI. With every click, a machine learning system will learn to analyze a consumer’s patterns and learn what a consumer likes and wants.
Another feature that is being implemented by more retail companies is AI chatbots. AI chatbots help answer questions that buyers have and work as an additional tool for customer assistance.
From medical records to patient data, the health industry has to document large amounts of data. Machine learning can filter the massive amount of data available to help provide new findings for important health issues.
According to an article from the New York Times, a cardiologist from the University of Colorado School of Medicine used machine learning to find patterns in patients who had heart disease. Machine learning allowed him to filter through thousands of patients and also look at the data objectively.
Machine learning algorithms have also been used to detect some instances of early-stage melanoma, according to an article from MIT News.
The Importance of Machine Learning
The internet and new technology constantly bring in new data through customer and company data. Knowing how to filter and analyze data is incredibly important for businesses that are looking for ways to stand out and harness digital resources.
Machine learning makes sense of thousands of sets of data. Not only is machine learning important for artificial intelligence, but it constantly works to improve results and can be a key component to decision-making and future investments.
If you’re interested in pursuing a career in machine learning, a strong background in data science can help to kickstart your career. Learn more about the data science curriculum developed by WOZ here.
Sophia Acevedo is a journalist based in Southern California. She is a 2020 graduate from California State University, Fullerton, and a proud Daily Titan alum.