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Common Machine Learning Techniques Used in Industry

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If you spend any time around data, you can probably guess that it’s going to be a big deal in the coming years. But what exactly is all this data and what are we going to do with it?

The truth is that there are so many answers to these questions right now; however, it’s not always easy for people outside of the industry to understand.

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Just take a look at some of the areas where data has had the most dramatic impact in the last few years: credit scoring , marketing, social media, and artificial intelligence. These fields have so much in common because they use machine learning—a type of artificial intelligence used by businesses and organizations today.

Machine Learning Techniques

For example, if you’ve ever bought anything online, then you already know about how tracking cookies work on websites to analyze your browsing habits and target ads accordingly. Or if you’ve ever searched for something using Google Search, then you also know about their understanding of natural language queries like “How do I get healthier?” Let’s take a look at some specific examples of how machine learning is being used in other industries as well:

Credit Scoring

One of the most important pieces of data for a bank is a customer’s credit score. It’s used for determining a customer’s ability to pay for the product or service they’re interested in. If a company wants to have a chance at selling you a new car or a mortgage on a house, they need to see that you have the means to pay for it. That’s where your credit score comes into play.

Now, a lot of people might be wondering how a person’s credit score is determined. The short answer is, it’s mostly based on data. Similar to how other companies use cookies, credit bureaus track your credit history and combine it with your financial information to determine your credit score. These bureaus can include information such as your credit card purchases, how much debt you have, how often you pay your bills on time, and how much debt you owe.

Marketing Automation

When we think about marketing automation, we often think about email and CRM marketing. However, a lot of marketing automation tools include tools for social media, too. That’s because social media is a perfect channel for automation. That being said, marketing automation is all about using data to determine the best time to send emails, whether or not to send a newsletter, when to post on social media, and which posts to create. 

Basically, it’s about setting up a process where the emails and social media posts are consistently scheduled based on data. Perhaps one of the biggest benefits of marketing automation is increased sales. When an email is scheduled to go out at the best time for a customer, it’s more likely to drive a sale. Or if a customer sees a post on social media that was scheduled based on data, they’re more likely to click on it. That’s how marketing automation increases revenue.

Social Media Automation

In the same way that marketing automation can be used to drive sales on social media, it can also be used to develop social media strategies. Let’s say you want to increase the number of people who see your posts. With proper automation, you can schedule posts at the perfect times to reach the right people. In that same way, you can also use automation to determine which posts to create in the first place.

However, making those decisions based on data is crucial. That’s because social media is filled with too many posts. If you also take into account the fact that social media is a dynamic and ever-changing platform, then it’s even more important to use automation to determine which posts to create. That way you’re writing posts that are truly relevant to your audience. But if you set up automation to determine when those posts go live, you can write more social media posts with less work.

Natural Language Processing (NLP)

NLP, or natural language processing, is a machine learning technique used to understand and process data from human language. It’s essentially the ability of a computer to read and comprehend human language the same way a person can. That’s why it’s important for companies and organizations to understand natural language. NLP has been around for a long time and it’s often associated with language translation. However, it’s being used in a lot of different ways today. That includes areas like chatbots and voice recognition.

Conclusion

Machine learning is a type of artificial intelligence used in many fields today. Its goal is to create algorithms that can analyze data and use that information to make predictions. It’s especially useful for credit scoring, marketing, social media automation, and more. Because it’s used in so many fields and has so many applications, it’s important to understand how it works.

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