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How Is Machine Learning Changing? Featured

How Is Machine Learning Changing? "\u201cThe more that you read, the more things you will know. The more that you learn, the more places you\u2019ll go.\u201d\r\n\u2015 Dr. Seuss"

 Machine learning (ML) is altering the landscape of all segments and industries such as education, transport, healthcare, and entertainment, among others. It will impact operations in other areas such as housing, shopping and cars. This technology is used in robotic process automation and making predictions that give business decision-makers insight regarding operations. As machine learning technology continues advancing, here are some trends that prove that it is changing:

  • Regulation of data

The increase in the number of mobile devices has resulted in massive production of data. This is the reason why data has become an essential resource for any organization. The bigger challenge here, however, is ensuring that the data is relevant. With such a massive amount of data from diverse sources, there is a need for data to be sorted in terms of type and quality. From now on, expect an increase in the number of cloud solutions and data centers set up for this purpose to increase. Machine learning will be used in these data centers to categorize data as a way of enhancing efficiency.

  • Big data is intersecting with IoT

The internet of things (IoT) is another area that is quickly developing. According to Transforma Insights, more than 24 billion IoT devices will be produced by 2030, generating an income of more than $1 trillion. Machine learning is becoming interlaced with IoT to make IoT devices smarter and secure. This collaboration is advantageous to IoT, and AI as these devices generate massive data needed by both AI and ML to work effectively. There will be a stronger link between IoT and ML that will see devices becoming more sophisticated in the future. For example, in manufacturing plants, IoT networks can gather data that can be analyzed by machine learning algorithms to improve production and performance.

  • Marketing with the help of Machine Learning

Marketing is an important element in any business. It is only through effective marketing that a company can be able to withstand tough competition. It makes customers aware of a given brand and enhances visibility while ensuring that a given revenue target is met. With the diverse marketing platforms, it has become difficult to prove that a business is in existence. However, patterns can be extracted from user data, allowing the formulation of successful and effective marketing strategies. Machine learning algorithms are being deployed increasingly to mine data and generate patterns that are used in decision-making. This is anticipated to more than double in the future.

  • Faster computing power

Industry specialists are now considering the importance of artificial neural networks, that can help solve different business problems. AI and ML, in particular, can help in decision-making, therefore improving user experience. As the year begins, more breakthroughs in algorithms are expected, increasing the ability of organizations to make more accurate decisions and at a faster pace. However, with this advancement, there will be a rising demand for privacy and knowledge on machine learning and its capabilities. This is the only way of building trust and triggering growth. This cannot be accomplished without adequate computing power, which increases processing speed. Once businesses have found the right machine learning algorithms, it is crucial to have more power centers to provide the hardware and software required for faster processing.

In a nutshell, machine learning will be functionally immense this year than it was in 2020. With the advancements in other areas such as IoT, machine learning will help handle various tasks maintaining accuracy and making faster decisions than ever before. These are important for the success of businesses, the majority of which want to satisfy their customers.

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Scott Koegler

Scott Koegler is Executive Editor for PMG360. He is a technology writer and editor with 20+ years experience delivering high value content to readers and publishers. 

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