What is Machine Learning?
Machine learning is a data-driven field of study in which, a machine learns from experience and examples, without being programmed. Hence, as opposed to traditional software systems that involve a program that governs the way the machine responds, in machine learning, the machine builds the logic based on the data that we feed to it. This works in a way that the machine becomes more efficient with time and experience.
Why has it become so popular?
Most industries today are driven by data. The volume of data generated on a daily basis has increased exponentially since the introduction of the internet and it continues to increase even today. As we now have rich data sources to build models, it has become necessary to build models that solve problems in high-dimensional data and add value to businesses in terms of insights. Hence, machine learning has become a necessity in every aspect of business be it marketing – predicting customer demand, operations – decision making related to demand forecast data, finance – trends in the stock market, and so on.
Pros
From finance and transport to healthcare and education, machine learning has grown to every nook and corner of the world of business. From self-driven cars to security drones, the real world applications of machine learning are endless. Machine learning makes it easy to identify trends and patterns in data. It can easily identify causal relationships amongst the data. Machine learning models improve over time. Therefore, we can say that in a few years, the businesses with machine learning will be far more advanced than those without, although today the difference may not be considerable.
Cons
Errors occurring in capturing data may generate flawed results in the later stages of machine learning applications. This is how sometimes recommended items on e-commerce websites are completely unrelated to the item being viewed. This issue requires human intervention as machines are not that smart. Machine learning cannot produce beneficial results instantaneously. It takes time and resources for the results to start showing.
Concluding remarks
Machine learning facilitates instantaneous adaptation. Machine learning, being automated, saves money and time. At the same time, entire system is under the control of a machine. Although this eliminates the need for a human developer, it requires a human to implement the changes or correct errors timely that cannot be done by the machine. As a result, machine learning is not necessarily right for every company or business. However, most businesses are likely to benefit from it.