You might have heard about the terms Artificial Intelligence, and Machine learning. Machine learning has been changing many things around us. Already, there are many use cases, in which, we are using or experiencing Machine learning either knowingly, or unknowingly.
A few decades ago, the miracles happening today in the world of technology would have seemed to be impossible, and now it is reaching new heights every day. In many areas, Machine learning is being used to solve different problems, and do different things, which were either very time-consuming and tedious or nearly impossible for humans.
In this article, we are going to have a look at some real-world applications of Machine Learning, which are just a demonstration of how big and amazing machine learning is, and give an idea of how far these things can go.
Applications of Machine learning in the Real world
1. Product Recommendation
If you have used some online shopping websites, like Amazon, or Flipkart, to buy some products, or even just see them, you might have seen some product recommendations relating to your search, buying history, and buying behavior, like stating that “the people who bought this, also bought …”.
For example, if you are trying to buy a mobile phone, and the buying behavior associates that when people buy mobile phones, they are more likely to buy wireless headphones as well, so you are likely to be shown with wireless headphones as well.
This is not magic, but the product recommendation related to your searches, the buying history, and the buying behavior, through which, the companies can recommend different products.
2. Self-Driving Cars
Around some decades ago, if you had said to someone, that the cars will drive on their own, they would have said to you, that either you need some good sleep, or you have gone mad. But today, we can certainly see the car driving by themselves on the roads. This is not some magic, but one of the wonders of technology.
We would not go into much technical detail to understand how self-driving cars work, but we can understand that there is not some ghost driving the car, but the model is trained to drive the car on its own. One such example of self-driving cars is none other than Tesla.
The self-driving cars have changed many things, related to transport, making it possible and comfortable for convenient long-distance journeys, and removing human error in driving. Using a lot of data for training, sensors and other equipment, and technologies, it is made possible for the vehicle to have a 360-degree view of the surrounding all the time.
So, if you find this interesting, you can explore more about self-driving cars. But self-driving cars can give us the vision to imagine how far these things can go.
3. Virtual Assistant
Ever imagined that you would have your own personal assistant on your mobile or some other device, which would be able to do many things, like making a phone call, setting up an alarm, setting up reminders, and much much more?
You might have heard about some virtual personal assistants, like Siri, Alexa, Ok Google(Google Assistant), etc. These are very useful in different cases, especially, in making your phone really hands-free and giving you an Iron Man-type feeling.
Anyways, this demonstrates to us how easily and humanly we can interact with our devices, to do different stuff, and it unlocks more possibilities ahead.
4. Machine learning in Healthcare
Machine learning is also being used in the healthcare industry for doing many things. By using machine learning, we can analyze patient records, and reports, predict diseases from some early symptoms, predict patient outcomes, create possible treatment plans, and much much more.
Using machine learning in the Healthcare sector can improve efficiency over many things, making it one of the useful applications of machine learning in action. The thing is that we have an enormous amount of patient data and history of records, through which, many possible tasks, like treatment plans, patient outcomes, and disease detection at some early stage can become possible.
5. Image Recognition
Image recognition comes out to be another interesting and useful application of Machine learning. Just imagine that you had many photos on your phone, and you had to group them together. It would be kind of tedious or at least time-consuming work for you, but thankfully, it can be done through machine learning. If you have heard of the Google photos application, or even used it, then you would be able to relate to it.
It does group the photos together like this person is there in all these photos, or these photos seem to be similar, or these are all the photos of mountains, or these photos are of the sky, of dogs, of cats, and so on. After that, it can be labeled as nature, people, pets, etc.
Image Recognition can be also used in things like face detection, face recognition, and much more.
Imagine that you love to watch movies on platforms like Netflix or Amazon prime, and because you have watched some of the movies, you are recommended some more movies, that you might wish to watch. If that has ever happened to you, you would relate to this application.
Many video streaming platforms use recommendation models, to recommend some new content, which you might find interesting. This can be based on many things, like your watching behavior, your search history, or your Wishlist of videos or movies. We won’t go deep into that, but we can understand that by observing our watching or searching behavior, these applications can recommend to us some content that we might like to watch.
This is like providing some of the options for you to watch, based on your interests, so that once you are on the platform, you do not need to think much about – “hmmm… what should I watch today?”.
7. Songs Recommendation
If you are a music lover, then song recommendation can be your best friend, in recommending you some songs that might fit your interests and listening habits. Many music streaming platforms use this song recommendation thing, to recommend songs to their customers, based on their interests and listening habits. So, this puts forward a new way to explore music, that too based on your interests.
8. Sentiment Analysis.
This is another interesting, useful, and sometimes life-saving application of Machine learning. Sentiment analysis can be understood as if we are trying to determine the emotional meaning of some communication.
For example, if you have a lot of movie reviews, and you want to analyze them as positive reviews, and negative reviews, you can perform sentiment analysis there. It can go far beyond that, but you can simply understand the big picture about the sentiment analysis, we can understand it as determining the emotions behind some communication.
9. Spam Detection
If you use email a lot, then you might relate to this spam detection thing. Imagine if there was no spam detection, each mail would come to the mailbox, and it would result in a flood of mail, out of which many are actually not important or spam(like some promotional or advertising emails). There are many factors that are considered in order to mark some emails as spam or not spam.
We are not going into the very technical details of this thing, but surely, it helps a lot, and it keeps away most of the spam emails so that we can focus on the important things.
10. Fraud Detection
As the name suggests, here, it is detected whether the transaction is fraudulent or not. Well, this is a very useful, and a kind of life-saving feature, because many scammers are out there, trying to steal your hard-earned money, but thanks to machine learning, through which, we can know if the transaction here is fraud or not.
We again won’t go into many technical details, but we can understand that by considering different parameters, we can get a prediction about whether the transaction is fraudulent or not.
In this article, we have seen some interesting and real-life applications of Machine learning, which many of us are using either knowingly or unknowingly. The thing is that Machine learning is growing with time, and helping us more and more in different areas.
If you are interested in knowing more about machine learning, you can follow us, and if you are interested in learning Python, you can visit our website, and learn Python programming language, after which, you can learn and explore things related to Machine learning.
FAQ related to Applications of Machine learning in real world
Ans: Machine learning can be understood as if our machine learns from the data, to make some predictions, or decisions, without being explicitly programmed.
Q: What are the different types of Machine learning?
Ans: On the basis of required supervision, we can classify Machine learning as follows –
1. Supervised Learning.
2. Unsupervised Learning.
3. Reinforcement Learning.
4. Semi-Supervised Learning
Q: What is Supervised learning?
Ans: Supervised learning can be considered as a type of Machine learning, where we are working on the labeled data, which means that we train the algorithm on a labeled dataset. In simple words, we can say that the machine learns under supervision.