Top 2021 Machine Learning Trends to Watch Out For

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Machine learning is a unique technology that is becoming popular with time. Today, it is teamed with artificial intelligence and adds immense value to the tech industry. Many companies have used this successfully in their business. For example, Google and more companies, including Netflix, have integrated ML algorithms to get deeper insights from their customer data.

What is machine learning?

Machine learning is a sub-category of artificial intelligence that focuses on creating applications capable of learning from specific data sets. Artificial intelligence is the branch of computer science that involves building machines with the ability to perform tasks requiring human intelligence.

Applications built using machine learning methodologies enhance their accuracy over a while. Moreover, these applications can achieve this feat without human beings having to program them to do so.

Machine learning involves the development of software programs that can access massive volumes of data. The programs can then utilize this informationtolearnto perform various complex tasks themselves.

Machine-learning trends in the post-pandemic era

Companies of all sizes have seen a disruption in commercial operations with the outbreak of the Covid-19 pandemic of 2020. As a result, these enterprises have to rethink and re-adapt their business strategies to the emerging market scenario.

The silver lining in this bleak situation is almost all of these organizations adapting machine-learning business models and practices. Taking this step enables these companies to satisfy their customers’ growing demands by offering them a better buying experience. This enables the companies to retain their competitive edge over other businesses to dominate the market.

Machine-learning – top trends for 2021

  • Hyper-automation

Hyper-automation involves using machine learning, robotic processing automation and artificial intelligence technologies to perform tasks humans would previously do. It is known as the next stage of digitalization. Many companies are embracing hyper-automation in the post-pandemic era to free their employees from performing repetitive low-value tasks.

These organizations can then use the insight and inherent talent of these staff members in other critical areas of their businesses. This helps to boost internal productivity and after-tax profits. Innovative products that multi-billion-dollar technology company Amazon.com Inc. introduces like Alexis an ideal example of the post-pandemic ML trends in hyper-automation.

  • Business forecasting and analysis

Credible experts from the esteemed name in database management and administration, RemoteDBA, state that time series analysis has been an integral part of the companies’ business forecasting strategy for many years. Time series refers to the sequence of specific data points which occur in consecutive order for a certain time.

These companies employ experts to look for and examine distinctive patterns in data sets. Theythen explain the patterns to their employers to help them make smarter business decisions.

In the post-pandemic scenario, advanced machine-learning solutions are taking time series analysis to the next level. The solution’s ability to identify and accurately forecast hidden patterns in data sets is helping companies improve their decision-making process.

  • The merger of the Internet of Things (IoT) and machine-learning

The Internet of Things or IoT is the physical objects like sensors and software companies use to connect to devices to exchange data via the Internet. In the aftermath of the Covid-19 pandemic; these enterprises integrate machine learning and artificial intelligence solutions to the Internet of Things technology.

The outcome of this trend is the introduction of ultra-modern electronic devices which are smarter and more secure. Even in the industrial sector, the merger of machine learning and the Internet of things makes manufacturing plants more productive. This is because the Internet of things network gathers the relevant data while machine-learning solutions analyze the trends to boost productivity.

  • Automation

Automation refers to the introduction of software technologies to replace human intervention in the execution of business processes. Implementing machine learning and artificial intelligence solutions are accelerating automation in many companies in post-pandemic scenarios.

This recent trend enables these enterprises to streamline the workflow in some of their most critical business processes. As a result, the organizations are noticing a significant increase in overall internal efficiency. This has ultimately led to a substantial rise in after-tax profits for the companies. Most companies are even not able to allow their employees to discharge their duties from their homes.

  • Boost in computing power

Ground-breaking algorithms are leading to the pragmatic development of ultra-modern problem-solving solutions which use machine-learning technology. Furthermore, these systems are capable of operating in standalone, cloud-based and even hybrid platforms. As a result, there is an increase in the number of corporate third-party service providers offering their clients these cloud-based machine-learning systems.

Most of these customers are companies. The algorithms can analyze and recognize distinctive patterns on vast volumes of data. The proper interpretation of the patterns using machine-learning technologies allows companies to make smarter and decisive business decisions. This enables the organizations to conduct their commercial activities to lead to a significant increase in revenue.

  • Cyber-security

Cyber-security is an important area where machine-learning solutions are making a significant contribution. In the aftermath of the Covid-19 outbreak, there has been a considerable increase in various forms of cyber-crimes. Companies of all sizes have come under threat from criminals launching ransomware, malware, denial-of-service and other forms of cyber-attacks.

On the recommendations of their Chief Information Security Officer and other IT specialists, these enterprises are implementing machine-learning solutions to identify anomalies in their business systems. This helps organizations trace suspicious Internal Protocol (IP) addresses trying to access their computer networks. This acts as a catalyst in enabling the companies to avert all forms of cyber-crimes.

The above are the top ML trends for you to watch out for in 2021. Businesses should pay attention to ML and incorporate it in their applications for persistent growth. In this way, they can optimize its benefits and reap more revenue. Market research predicts that the global arena for machines learning currently valued at nearly $7.3 billion (last taken in 2020) is expected to expand to $30.6 billion by 2024. This is incredible news for machine learning technology and displays an upward curve in 2021 and beyond for this technology.

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