Uses of Machine Learning

Introduction To Machine Learning

The following article provides an outline for the Uses of Machine Learning. Machine learning is an evolving and fast-growing field of science and technology. ML and AI are part of our daily life, whether we are using them knowingly or unknowingly. One of the best examples of ML use cases is Gmail putting different emails in different buckets like primary, promotions, updates, social media, and spam.

What Is Machine Learning?

In a nutshell, Machine Learning can be understood as:

“Machine learning (ML) in the field of Science Technology, which leverages the knowledge of statistics & mathematics for algorithms to go through data and learn about features by assigning coefficients to each feature without coding any explicit instructions. Machine Learning algorithms find the patterns available in data and, based on that predict the outcome.”

Uses Of Machine Learning

There are numerous use cases of Machine learning, some of them are as below:

• Fraud Detection: It is used in many organizations where transactions are taking place. Banking sector where it becomes crucial to identify Fraud transaction and limit it as much as they can.
• Spam detection: Nowadays, there are lots of viruses are sent over email, and fake emails do come across. For any organization or individual, it is very important to keep their data safe and stay away from fake news. Otherwise, it can cost the loss of information, time, and money.
• Image Recognition: Ever noticed Facebook suggesting tagging a person in a photo you just posted on your Facebook profile? How does Facebook knows this person if there are 5 people and all of them are on Facebook, you would get the option to tag all? Well, this is what image recognition is. A machine can identify the person by name in an image. How cool is that?
• Voice Recognition: Heard about Alexa and Siri. Yeah, they understand your instructions as you say and then work accordingly. If you give the command to play a song, “they shall be done,” and music will be played, of course, the song shall be available somewhere online.
• Sentimental Analysis: Humans are emotional. They are driven by sentiments, say 10 bad things about a good product, and no one would buy that, and say 10 good things about a bad product, people would still buy it. because of their sentiment, they would choose the first product. ML is applied for sentimental analysis on Amazon, Flipkart & Twitter.
• Recommendation Engine: Buy an electric appliance on Amazon, and it will recommend buying similar products, or watch a video on youtube you will get a recommended video. All job is done by recommendation engines.

Importance Of Machine Learning In Today’s World

• In today’s fast and evolving era, the competition is tough, and to keep up with the need of users, one ought to have the best user experience.
• User experience is something of an emotional thing, and it cannot be hardcoded.
• But Machine learning is setting up the bar high by learning from the existing information to provide a better experience to users, which is something awesome.

Conclusion

We are surrounded by technology that uses ML, and we are making use of it knowingly or unknowingly. If you are on any social media platform or just using Google to search for anything or you are making use of Google Maps, everything is tracked with your unique ID in the case of Google; it’s your Gmail Id, etc. This information is then used to provide better recommendations to the user according to their geography, age, and interests.

Recommended Articles

This is a guide to the Uses of Machine Learning. Here we discuss the introduction to machine learning with importance in today’s world and its uses. You can also go through our other related articles to learn more –

1. Machine Learning Tools
2. Machine Learning System
3. Machine Learning Models
4. Applications of Machine Learning