“The apps are listening to us!”, screams Suzie as the pink sweater she’s been talking about magically turns up in her “recommended for you” section!
Suzie, Oh Suzie!
Are you sure it’s not because you have an affinity to the colour and an uncontrollable urge to shop at the beginning of every month?
If only someone had told her about the power of Machine Learning algorithms.
Every time a food delivery app reads your mind or your Pinterest boards turn into notifications from shopping sites, you can’t help but blame the incoherent terms and conditions you signed, or feel like the tech giants are controlling your life!
But all they’re doing is using a technology that’s been making waves for a while- Machine Learning!
What is Machine Learning?
Machine Learning is an innovation that has enhanced human lives through industrial and professional processes. Machine learning is a subset of artificial intelligence, which aims to improve everyday lives.
Machine Learning has become a buzzword in the world of technology which is growing rapidly. Currently, machine learning is used in multiple industries, ranging from medical diagnosis, image processing, prediction, classification, learning association, regression, etc. Here is the most popular real-life application of Machine Learning:
Real-Life Applications of Machine Learning:
1. Self Driving Cars
“Tesla” is one of the most searched terms in the recent past. This exciting invention uses various facets of machine learning to train cars to detect people and objects while driving.
2. Dynamic Pricing
Fixing the right price for any goods or service is an age-old problem. Economic theories have developed many pricing strategies that depend on demand and supply. Machine learning has enabled dynamic pricing for everything ranging from plane tickets to cab ride fares. This has been made possible by tracking buying trends and determining competitive product prices.
3. Voice Assistants
Today, we have various personal assistants like Google Assistant, Alexa, Siri, etc. They help us in various ways by just our voice instructions. They record our voice instructions and send them to the cloud server and decode the same using ML algorithms.
The voice assistant records the voice, which is then converted into text. It is fed to a natural language understanding engine that interprets the meaning and fetches the required action, which is sent back to the voice assistant. From there, the voice assistant knows what to do next!! It simply carries out the task you asked for.
4. Recommendation Engines
Machine Learning is majorly used for product recommendations by e-commerce and entertainment industries. For example, whenever we search for a product on any e-commerce site, we start getting advertisements for the same. This is because of the machine learning algorithm. Other giants such as Netflix use the same.
When we login into Netflix, the homepage is filled with the shows that Netflix recommends you to watch. Right from the recommendations to thumbnails and streaming quality, Netflix uses machine learning to provide subscribers a better watching experience. Similar is the case with Spotify!
( Are you listening, Suzie? )
5. Social Networking Sites
One of the earliest applications of Machine Learning in social networking sites is automatic tagging suggestions. Social sites use face detection to find the person which matches with the database and suggests the person. All the social media and each post over the internet is regulated which ensures that it follows the policies and doesn’t encourage or promote sexuality, nudity, any form of violence, or harassment.
6. Traffic Prediction & Alerts
Everyone is using Google Maps today when they are on the go to explore a new place, to find the shortest route, and know traffic level. This is made possible by the use of Machine Learning, which works like this:
To predict what the traffic looks like, Google Map analyses the pre-existing traffic patterns for the route over time. Then it combines that database of the historic patterns with the real-time traffic conditions and generates predictions based on both data sets. People using such apps also contribute to making it better. The information is collected and sent back to the database for improved performance.
7. Commuting & Travel
Apps like Uber and Ola are classic examples of real-world applications of Machine Learning. These apps automatically detect the current location and provide options for the frequently visited places based on history. It also identifies the available drivers nearby and estimated time and fare for the commute.
8. Fraud Detection
Online transactions have gained much popularity among people for their ease of use. It is Machine Learning that makes the transactions safe and secure. Fraudulent transactions can take place in different ways like fake accounts, ids, or stealing money in the middle of the transaction. All these are detected and secured with the help of machine learning. ML has a specific pattern for genuine transactions which gets changed for fraud transactions.
9. Online Video Streaming
With more than 100 million subscribers, Netflix is one of the biggest players in the entertainment industry across different languages. This is possible with machine learning. There’s no denying that Netflix has a huge customer retention rate, and the credit goes to ML.
The algorithm constantly keeps on gathering a massive amount of data including when they pause, fast forward, or rewind. A major focus is also given on collecting data about the type of content watched, ratings given, and the browsing/ scrolling behaviour. These data are collected for each subscriber and processed for the recommender system.
10. Google Translate
Google Translate is also an application of machine learning which helps us by converting the text into an asked language. The technology used in this is the sequence to the sequence learning algorithm.
Takeaway
So these are some of the most popular examples of machine learning applications in real life. The possibilities of the application of machine learning along with technology are evolving at a high pace. With the increasing demand for machine learning, organizations are in search of professionals who have thorough knowledge about these technologies.
In short, we can say that Machine Learning is making an incredible ground-breaking growth in the field of AI. Machine learning isn’t easy to grasp, but even without technical know-how, there’s no denying the power of all the varied applications of machine learning.