What is Machine Learning?

In simple words, Machine Learning (ML) is a branch of AI and computer science that provides the ability to automatically learn and improve from experience without accomplishing a change manually to the systems. Machine Learning targets on the use of data and algorithms to mimic the way that humans learn.

In the world of Artificial Intelligence, it is considered to be one of the most exciting technologies that one would have ever come across. The actual definition of Machine Learning is evident from its name, i.e., “The ability to learn”. Without knowing it, people all over the world are using Machine Learning on their day-to-day lives.

What is Machine Learning used for?

If you are curious to know what is Machine Learning used for, then we are here to let you know about it. Machine Learning is used in multiple fields, industries and a vast variety of applications such as in medicine, image and speech recognition, email filtering, traffic prediction, internet search engines, online fraud detection, banking software to detect unusual transactions, stock market trading, automatic language translation and computer vision. As you can see ML can be used for all these above-mentioned purposes where it is challenging to develop conventional algorithms to perform the needed tasks.

Examples of Machine Learning

The Examples of Machine Learning are:-

Image and Speech Recognition: These are one of the most common uses of ML. Image Recognition is the ability of software to identify objects, places, people, writing and actions in images. Speech Recognition is the ability to translate spoken words into the text. The common goal of image recognition is to classify detected objects into different categories. It is also known as object recognition. Speech recognition focuses on the translation of speech from a verbal format to a text one whereas voice recognition just seeks to identify an individual user’s voice.

Medical Diagnosis: Machine Learning can detect patterns of certain diseases within patient’s electronic healthcare records and inform clinicians of any anomalies. By its developing algorithms it provides information to the machine that can help in imaging and analyze human bodies for abnormalities. Hence, Machine Learning is making healthcare smarter.

Prediction: With the help of Machine Learning, GPS navigation predicts traffic ratio through central traffic managing servers. Businesses use ML in order to recognize patterns and then make predictions about what will appeal to customers and help make a better product.

Finance: Data scientists are always working on training systems to detect flags such as money laundering techniques, which can be prevented by financial monitoring, enhanced with ML. Algorithms of Machine Learning can be used to detect transactional frauds by analyzing millions of data points that humans might miss.