10 Real World Problems That Machine Learning Can Solve | Icore
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10 Real World Problems That Machine Learning Can Solve

Machine Learning is one of the modern-day technologies, which was also just an idea a few years back. None of us ever believed the fact that our vision can be evolved to a point where it starts to feel like science fiction. But we have narrowed the possibilities as we are getting closer to automation by building intelligent machines capable of performing tasks without any human touch or intelligence.

It all started in 1943 when the brilliant mathematician Alan Turing created “The Bombe,” a machine that was cracking a staggering total of 80,000 Enigma messages each month. Not only did it help Allied Forces win World War II, but it also asked a simple question “Can machines figure out ideas on their own?”

We strongly believe that introduction of Artificial Intelligence and its sub-parts like Machine Learning is the answer to that question. Today we are not talking about one of the trending advances in technology which is hot today and forgotten tomorrow; we are discussing Machine Learning which is here to stay and make lives easier on both ends. You might have no idea about “Machine Learning,” but after reading this blog, you will know how it shapes and streamlines the way we work, live, and communicate, in short, “Our Future.” 

What is Machine Learning?

Machine Learning is a sub-array of artificial intelligence where computer algorithms independently learn from data and information without any human intervention. It’s a practice of using built-in algorithms to analyse data and further learn from it. 

The objective of machine learning is to adapt to new data independently and make decisions and suggestions based on thousands of calculations and analyses. As it is a sub-part of artificial intelligence, the process is accomplished by infusing deep learning applications and AI machines from their fed data. 

How Do Problem-Solving And Machine Learning Co-Relates?

The basic definition of problem-solving is to find the most accurate process of finding solutions to complex problems. When we look at the ML, then it is pretty vast and is expanding rapidly. How do problem-solving and machine learning correlate? 

In 1977, Tom Mitchell shared a “well-conditioned” definition to the ML, which we believe is the perfect representation of today’s market scenario and how we can use ML to make things easier for businesses from all around the globe. He stated, “An ML is a computer program which is said to learn from experience E to some task T and some performance measure P, if its performance on T, as measured by P, improves with experience E.”

So, suppose you want your program to predict something, for example, identifying a person from a group of individuals using their interaction methods (task T). In that case, you can feed every individual’s way of interaction data (experience E) to a machine learning algorithm. It will successfully learn to PREDICT the individual pattern through their respective way of interaction (performance measure P). It means you are always one step ahead as you already know what they might say or do. 

With the inclusion of machine learning in your business, you can use the previously gathered data from your industry to develop better ways than the existing solutions using Machine Learning. The main objective of ML is never to make “perfect” speculations because ML trades in domains. Its main goal is to come up with good enough estimates so these predictions can be helpful in different ways. 

Who’s Using It?

The principal element of machine learning is data. All the major industries that work with large amounts of data have already acknowledged the worth of machine learning technology. With endless data, you have endless possibilities. It opens gates to many practical ways that can help scale your business to further domains. By gathering valuable insights from this data, organizations are finding a more efficient way to work and gaining an edge over their competitors.

Some of the top industries in the world that are currently using Machine Learning are: 

  • Financial Services

Banks and other financial institutions in Singapore are using ML for two key purposes: preventing fraud and identifying essential insights in data.

  • Transportation

ML has already become a crucial prospect to delivery companies and other transportation enterprises. They use it to analyze data to identify patterns and even trends, making routes more efficient and even predicting potential problems to increase profitability.  

  • Health and Care

Health Care is also reaping the benefit of ML as it is helping medical experts analyze data to identify patterns to offer better diagnoses and treatment to the patients. 

  • Retail

Ecommerce has already become part of our daily lives. Retail businesses are using ML to recommend items that users might LIKE by analyzing their previous purchases.

  • Oil & Gas

Machine learning in the Oil and Gas industry is immense and will expand to various factors very soon. It is currently being used to detect new energy sources, analyze minerals in the ground, and even anticipate any kind of refinery sensor failures. 

10 Real-World Problems that Machine Learning can solve           

1. Recommending Products after Collecting Previous Data

Recommendation systems are one of the most common machine learning use cases in day-to-day life. These systems are used mainly by search engines like Google and Bing and the top eCommerce platforms like Amazon and eBay.

The ML integrated systems show a list of recommended products individually for each of their consumers. These suggestions are based on data like previous purchases, wish lists, searches, clicks, inquiries, and browsing history. This data is fed to a comprehensive ML algorithm to strike the user at the right moment and enhance their customer engagement. 

2. Works as the Best Image and Video Recognition Tool

If you have come across features like face recognition, text detection, object detection, and landmark detection, it is because of the integration of deep learning in machine learning. When ML algorithms are trained with innovative deep learning frameworks, they can quickly identify and classify objects and make things easier for a non-native person.

MNL can also be used to determine handwritten text by segmenting a piece of writing into smaller images, each containing a single character. 

3. Your Virtual Assistant

A virtual assistant, which is also very common as an AI assistant, is an application program that comprehends natural language voice commands and finishes the tasks for the users like searching the web, booking an appointment, etc. If you have also asked Google Assistant in your android phones to wake you up at 5 AM or asked Siri on your iPhones for directions to the nearest restaurant, then ML has also made your life easier.

Some principal personal assistants or smart assistants available in the market are Siri, Google Assistants, Alexa, Echo, and Google mini. These assistants can help you look for information by voice commands or answer your questions by searching your query on the web. 

4. Ingenious Gaming Using ML

With the advancement in technologies, we can improve the graphics of the games and give them a mind at the same time. Lately, if you have been facing difficulties beating the bot in a chess game, then ML might take it over. Today’s games not only simply analyze your moves but are also learning how to play the game better than you by practising numerous times. Now using your mind against such an intelligent system will surely give you brains and make you smarter at the same time. 

5. Devising Superior Health Care Methods

Even hospitals are utilizing machine learning to cure and treat patients. Thanks to our wearable devices, doctors can get accurate data on our health from anywhere in the world and suggest an aid if they find something helpful. The integration of ML in some essential tools can quickly provide real-time insights and combine with the explosion of computing power. 

It can help doctors to diagnose critically faster and more accurately. Not only this, AI is assisting in the development of new medications and treatments, predicting harmful reactions at the early stages, and working towards finding a way to lower the costs of healthcare for providers and patients. 

6. Protecting Environment in the Most Impactful Way

Aforesaid, possibilities are endless with ML, and it’s just the beginning. Recently IBM’s Green Horizon Project was acknowledged by experts worldwide as it accurately predicted weather and pollution forecasts. We can use it to save and predict natural forecasts with the expertise of the professionals from Singapore by our side. It is helping city planners to run every kind of scenario just by feeding previous data to their ML algorithm to find ways for minimum environmental impact. 

7. Real-Time Dynamic Pricing

You might have already encountered this scenario while booking a flight ticket to travel on Christmas or booking a cab at peak hours. You will notice a big gap between the regular pricing and pricing at that particular time. So, in these scenarios, the ML and data analysis techniques are helping businesses to get to know more about their users. It answers two critical questions. 

First, how are customers reacting to surge prices? And second, whether they are looking for customers because of surge pricing? The integration of AI and ML helps the businesses and the users as it helps determine when customers are looking for the best promotional and discounted prices. 

8. Innovations in the Finance Sector Including Stock Market

The functioning of the finance sector is about to change in the upcoming years completely. Thanks to technologies like mobile app development and machine learning, the stock market is at its all-time high. 

Thanks to AI, deep learning, and machine learning, it has become easy for users to predict the market price by feeding it the previous data. It will allow traders to make better and steady decisions which means less financial loss. Not only this, the machine learning-based anomaly detection models can easily monitor your every transaction request and alert you of any kind of suspicious activity.

9. Commute Predictions Using Machine Learning

Almost everyone uses GPS services while driving. A programmed GPS helps us in finding the proper navigation to our destination. But it’s the integration of ML and its features like congestion analysis GPS that helps us by telling us the path to avoid traffic and reach our destination on time. It saves the data like our location and velocities of the vehicles on the same path to determine the traffic and let us know whether it would be the right path to follow. 

10. Online Video OTT Streaming Applications 

The pioneers of online video streaming services are Netflix and Amazon Prime; both of them combined have killed the traditional way of watching television. But how were they able to keep the customer engaged on their platforms? First by offering impressive content, secondly by getting personalized with the users. 

They were able to capture mass audiences using machine learning. At the right time, they integrated ML in their program and fed it the user’s data like day and time they watch content, type of content they like to watch, browsing pattern, whether they like to watch trailers before they watch a movie or a show, etc. They are using practical machine learning frameworks to engage their audience by providing quality streaming service right to their homes. 

Conclusion

The possibilities with machine learning are limitless. All you need to do is find a comprehensive way to use it in your particular business domain to improve your services. Sometimes it can be indispensable to understand the problem at hand, as you can’t use any ML algorithm for your business needs.

Every problem is different from the previous one in machine learning. This means that you can’t just feed some data to a machine learning algorithm with a neural network and pray for the results.

Every situation demands a different approach and that is why it is crucial to consider looking for professional Machine Learning experts.

People who must have enough experience in the field and can work with an open mind to first understand your business requirements. And then come up with the incredible machine learning algorithm that benefits your business immensely without wasting anyone’s time. 

At iCore Singapore, you get all-inclusive Artificial Intelligence and Machine Learning Development services, redefining the way your business operates.

With the right mix of AI/ML development teams, you can trust us for high-quality solutions that cover all your needs.

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