Ways That Companies are Using Machine Learning

To the non-expert, machine learning may sound like wishful sci-fi thinking. However, companies around the world are using it in innovative ways to beat the competition. Smart managers realize that implementing machine learning has the potential to help their brands stand out. It is one of the fastest and cheapest ways to introduce efficiency and reduce costs. 

The machine learning industry has grown steadily. According to iTransition Machine Learning, companies will spend more than $430m in 2022, and this will surpass $500m in 2023. In America alone, business expenditure on machine learning technology is expected to reach nearly $25m during the same period. 

Already, more than one-third of all companies use machine learning in one way or another, and an additional 42% have indicated that they plan to introduce it into everyday operations shortly. 

Young people and experienced IT professionals who get high-quality training in machine learning development and implementation stand to gain. Job predictions for the coming decade are excellent. 

It is estimated that one out of every five workers relies on machine learning in their jobs. Companies need to hire experts to support them, and they are willing to pay well. 

A data science online master’s degree equips you with the skills that employers are looking for. The course teaches students how to work with large data repositories and understand parallel programming. They also learn how to use machine learning to make smart, data-driven business decisions. 

The course doesn’t take very long to complete, and you don’t need to have a background in computer science to be enrolled. Learning online gives you flexibility, which is vital for professionals who have to juggle work and study. 

Before you enroll, you may want to know what machine learning is all about and how businesses are using it to make better decisions. Keep reading to find out. 

What is machine learning, and what are some common applications?

Machine learning is a branch of data science that trains machines how to learn. The idea is that machines and systems can learn from data without being explicitly programmed themselves. If enough data is fed through machine learning infrastructure, it learns to identify patterns and can complete tasks competently without human involvement. 

This technology is all around us. Retail companies such as Amazon and entertainment businesses such as Netflix use it to recommend products that you may be interested in. They look at choices you have made in the past and use that data to give you recommendations.

Self-driving cars are another example of machine learning. Speech recognition apps such as Siri and Alexa rely on machine learning, as do Google Maps and taxi apps such as Uber. 

The spam filter in your Gmail account uses machine learning to trash emails that you may not want to see. The same technology is used to classify emails into different categories. 

In banking, machine learning is used to prevent fraudulent transactions. Every time you make a withdrawal or deposit, the information is fed into a program that can recognize patterns. If you go over your usual limit, the system triggers an alert to ensure that you are the one making the transaction. 

DigiXNews has an excellent post on emerging business trends in different industries. They are not entirely new ideas, but the common thread that runs through them all is reliance on machine learning and AI to improve products and services. 

How are businesses using machine learning?

Automation of everyday tasks

One of the best examples of machine learning is task automation. Online businesses, for example, send out thousands of emails every few days. It would be a momentous job to do this manually. Rather, they use machine learning technology to pre-program emails to be sent out on a certain day at a certain time. 

Chatbots

They may be annoying when you need to talk to a real human, but they eliminate the need for companies to employ people to chat with clients. 

The AI in chatbots identifies routine questions that users ask for you to pre-program the answer. Managers only have to deal with complex queries that the chatbot hasn’t been programmed to deal with.

Enhancing the customer experience

Machine learning uses recommendation engines to provide insights into the user experience. Imagine a business that has 1,000 active customers digging through their purchase history so that they can make recommendations for the future. It would require many hours and dedicated employees, both of which are valuable resources that could be used elsewhere. 

AI makes things easier. It scans customer history and gives recommendations based on purchase history. It also tells the business manager what they can do to improve individual customer experiences. 

Dynamic pricing

Businesses can use historical pricing information and other variables to understand what factors impact demand and set prices accordingly. 

The best example of this is Uber, which sometimes uses surge pricing. Taxi fares change automatically depending on traffic, weather and location. All this is done using machine learning. 

Customer segmentation

Imagine having to look at a business’s customer list to determine the geographic location of each buyer, where most sales derive from, what customers buy, when they are likely to buy it, and when they buy most frequently. 

It is a momentous task that would require, in some cases, entire departments working round the clock. 

Machine learning has eliminated the need for human input. Smart systems capture customer data and segment it, providing managers with a clear picture of segments, buying patterns and geographical locations.

These are just a handful of the ways that businesses use AI to improve decision-making, reduce waste and increase revenue. There are many more. 

Where can I enroll for a data science online master’s?

Many universities offer this post-graduate course, but you must make sure that you choose one with the right accreditations for your degree to be recognized by employers. 

Look into whether or not you can transfer credits based on your previous qualifications and work experience. It is also a good idea to look into course instructors. Find out whether they are recognized in their field. 

Conclusion

The use of machine learning in business is growing at a remarkable rate. Professionals who understand its use have an edge. They have excellent employment prospects with promising remuneration. A data science online master’s will teach you how to implement machine learning in business.