Machine Learning (ML) has become a buzzword for quite some time now, especially when discussions around futuristic technologies transpire. Cars that drive without human intervention, virtual personal assistants, automated detection of malware, refined search engines for improved search results, voice-driven applications with speech recognition – all are examples of machine learning to quote from our day-to-day life.  

With more enterprises recognizing what is machine learning and its various use cases, the market for machine learning-enabled solutions is growing exponentially. As per a market study, the global market size of machine learning will reach USD 8.81 Billion by 2022 from 1.03 Billion in 2016. It is expected to report a CAGR of 44.1% during the forecast period. With advancements in technology and the ever-increasing proliferation of data generation, the future outlook of machine learning solutions looks promising.

If you want to explore what is ML and the future perspectives of it, here is an informative read. To define machine learning for you, we shall analyze why it is becoming increasingly important in the current business world.

What is Machine Learning? 

To begin with, let us analyze the machine learning definition and the basic concept behind it. We know there is an exponential growth happening in data generation now, thanks to the Internet of Things (IoT), rising internet penetration, and advancing digital technologies. It is estimated that 463 exabytes of data will be created each day, globally, by 2025.

By tapping this enormous amount of data, organizations and governments can derive valuable insights and work towards progress. However, it takes a lot of resources and time to comb through such a massive amount of data manually. That is why Artificial Intelligence solutions are gaining attention. It is being deployed to gather, process, and analyze the accumulated data, exceedingly. Simply put, Machine Learning meaning is: A method of Artificial Intelligence used for data processing.

Going as per the Machine Learning definition, it is a subset of artificial intelligence that allows software applications to automatically learn without being explicitly programmed to do so. In other words, it enables computers to learn and improve automatically. The different types of Machine Learning algorithms rely on historical data to become more accurate in predicting outcomes.

What is Machine Learning Used for, and what are the Advantages?  

Machine learning is a technological tool that helps companies derive valuable insights, and make data-driven decisions across functions. By taking advantage of various types of machine learning algorithms, organizations can address different business challenges they currently face. They can make significant advancements in business quickly and cost-effectively.

Listed below are a few advantages of using different types of Machine Learning:

  • Review large sets of data to discover trends and patterns
  • Ensure rapid processing and analysis of data
  • Improved accuracy and efficiency with experience 
  • Handle multi-dimensional and varied sets of data 
  • Interpret past customer behavior 
  • Make predictions and improves algorithms on its own

Improving Business Prospects

Machine learning solutions are a boon for businesses looking forward to saving time and money. It can be advantageous in almost all business functions – sales, marketing, manufacturing, procurement, supply chain management, customer experience, and more. Moreover, it is very flexible and can be used in any industry vertical – from medical, finance, technology, manufacturing to entertainment. Major organizations worldwide have already started to explore what is machine learning and gain substantial business benefits through its various use cases.

Here are a few examples of applying machine learning for business benefits:

  • Effective Manufacturing – A vast amount of data is generated every single day in the manufacturing industry. By using intelligent algorithms, businesses can detect the peak and lull times quickly. They can explore ways for process improvements and work on improving cost-effectiveness. Using machine learning, manufacturers can reduce up to 30% of material delivery times and achieve 12% fuel savings. 
  • Enhance Customer Experience – A holistic view of the customer helps to understand their needs and make product enhancements accordingly. Machine learning is widely used now to gather and analyze data from varied sources and automate various aspects of customer experience. It can be well-used for fraud detection too.
  • Improved Accuracy in Finance – Machine learning solutions can be used for data entry and assessment in finance. By monitoring existing processes and patterns, it can recognize anomalies and nuances effectively; hence higher precision in accounting function can be achieved. 

An Economic Overview 

Properly knowing all about machine learning enables enterprises to automate a large number of tasks that are presently done by humans. When mundane and time-consuming tasks are done by machines, humans can focus on value-adding tasks and stay productive. For this reason, it is expected to have a significant impact on the global economy.

Machine learning is capable of unlocking unprecedented value in various business domains and drive economic growth comprehensively. A report from McKinsey shows that 82% of enterprises with machine learning and AI solutions have reported increased ROI. It is estimated that machine learning, along with artificial intelligence, has the potential to create an additional value of USD 2.6 trillion by 2020. 

Wrapping Up

In this blog, we have analyzed what is machine learning, and how it is gearing up for a revolution in everyday life. More businesses recognize that adopting machine learning leads to increased efficiency in logistics and manufacturing, improves sales and marketing ROI while ensuring better customer experience.

With machine learning making deeper inroads into our collective consciousness each day, machine learning engineers are highly-paid and are in-demand now. The job opportunities in machine learning and data science are expected to grow by 11% by the end of 2021. Here is the takeaway – the moment is right now to start learning what is ML and build your skills around it for better career prospects.