Machine Learning (ML) has proved to be one of the century's most game-changing technical advances. In today's highly competitive business setting, machine learning is allowing businesses to accelerate their digital transformation and step into the era of automation. Some of the well-known techies may even claim that AI/ML is needed to stay valid in certain industries, such as electronic payments, banking fraud prevention, and promote products.
So let’s understand what exactly we mean by Machine Learning (ML). Machine learning is a branch of artificial intelligence (AI) that allows computers to learn and develop on their own without having to be specifically programmed or configured. It is concerned with the development of computer programs that can manipulate data and learn on their own.
Machine learning is now used in some way or another in almost every other app and software available on the Internet today. Machine Learning has become so mainstream that it is now the go-to method for businesses to address a wide range of issues.
Speaking of the applications of Machine Learning (ML), let’s read further:
One of the most primary applications of machine learning is image recognition. It's used to recognize things like people, locations, and digital images. Automatic friend tagging recommendation on various social media platforms is a popular application of image recognition and face identification. For example, Facebook, the social networking maestro uses image recognition when we tag our friends on the posts. When we upload a picture of our Facebook mates, we get an automatic tagging suggestion with their names, which is driven by machine learning's face identification and tracking algorithm.
Another great application of Machine Learning is traffic prediction, say when we are traveling from one place to another, Google Maps is our top choice, which indicates the best path with the quickest distance and forecasts traffic conditions. Machine Learning does this in two ways:
Google Maps and sensors have real-time vehicle position.
Simultaneously, the average time has been taken on previous days.
Voice recognition, also known as "Speech to text" or "Computer speech recognition," is the method of translating voice commands into text. Machine learning techniques are now commonly used in a variety of speech recognition apps. The voice recognition tool is mainly used by most of the popular assistants such as Google Assistant, Siri, Cortana, and Alexa to obey voice commands.
Easy suggestions for products
Several e-commerce and entertainment services, such as Amazon, Netflix, and others, use machine learning to make product recommendations to users. Because of machine learning, if we search for a product on Amazon, we begin to receive advertisements for the same product when browsing the internet on the same browser. Using various machine learning algorithms, Google deduces the user's interests and recommends products based on those interests.
Online frauds have become quite common these days with all the UPI transactions and net banking facilities. By detecting fraud transactions, machine learning makes our online transactions safer and more stable. When we conduct an online transaction, there are several ways for a fraudulent transaction to occur, including the use of false accounts, fake ids, and the theft of funds in the middle of a transaction.
Machine Learning is the next big thing, every industry is using it to unleash its full potential. The approach starts with insights or data, such as examples, experience, or training, so that we can search for trends in data and make informed decisions in the future based on the examples we have. The primary goal is for devices to learn on their own, without the need for human interference, and to adapt their behavior accordingly.